A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems. - Kristina Lerman; Aram Galstyan; Alcherio Martinoli; Auke Jan Ijspeert (Artif. Life, 2001)

Mathematical Model of Foraging in a Group of Robots: Effect of Interference. - Kristina Lerman; Aram Galstyan (Auton. Robots, 2002)

Resource allocation games with changing resource capacities. - Aram Galstyan; Shashikiran Kolar; Kristina Lerman (AAMAS, 2003)

Agent memory and adaptation in multi-agent systems. - Kristina Lerman; Aram Galstyan (AAMAS, 2003)

Threshold Behavior in a Boolean Network Model for SAT. - Alejandro Bugacov; Aram Galstyan; Kristina Lerman (IC-AI, 2003)

Macroscopic analysis of adaptive task allocation in robots. - Kristina Lerman; Aram Galstyan (IROS, 2003)

Resource Allocation in the Grid Using Reinforcement Learning. - Aram Galstyan; Karl Czajkowski; Kristina Lerman (AAMAS, 2004)

Analysis of a Stochastic Model of Adaptive Task Allocation in Robots. - Aram Galstyan; Kristina Lerman (Engineering Self-Organising Systems, 2004)

Distributed online localization in sensor networks using a moving target. - Aram Galstyan; Bhaskar Krishnamachari; Kristina Lerman; Sundeep Pattem (IPSN, 2004)

A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems. - Kristina Lerman; Alcherio Martinoli; Aram Galstyan (Swarm Robotics, 2004)

Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms. - Wei-Min Shen; Peter M. Will; Aram Galstyan; Cheng-Ming Chuong (Auton. Robots, 2004)

Mathematical Analysis of Multi-Agent Systems - Kristina Lerman; Aram Galstyan; Tad Hogg (CoRR, 2004)

Comparative analysis of top-down and bottom-up methodologies for multi-agent system design. - Valentino Crespi; Aram Galstyan; Kristina Lerman (AAMAS, 2005)

Inferring Useful Heuristics from the Dynamics of Iterative Relational Classifiers. - Aram Galstyan; Paul R. Cohen (IJCAI, 2005)

Modeling and mathematical analysis of swarms of microscopic robots. - Aram Galstyan; Tad Hogg; Kristina Lerman (SIS, 2005)

Resource Allocation in the Grid with Learning Agents. - Aram Galstyan; Karl Czajkowski; Kristina Lerman (J. Grid Comput., 2005)

Relational Classification Through Three-State Epidemic Dynamics. - Aram Galstyan; Paul R. Cohen (FUSION, 2006)

Iterative Relational Classification Through Three-State Epidemic Dynamics. - Aram Galstyan; Paul R. Cohen (ISI, 2006)

Analysis of Dynamic Task Allocation in Multi-Robot Systems. - Kristina Lerman; Chris V. Jones 001; Aram Galstyan; Maja J. Mataric (Int. J. Robotics Res., 2006)

Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification. - Aram Galstyan; Paul R. Cohen (ILP, 2007)

Influence Propagation in Modular Networks. - Aram Galstyan; Paul R. Cohen (AAAI Spring Symposium: Social Information Processing, 2008)

Comparing Diffusion Models for Graph-Based Semi-Supervised Learning. - Aram Galstyan; Paul R. Cohen (MLG@ICML, 2008)

Analysis of social voting patterns on digg. - Kristina Lerman; Aram Galstyan (WOSN, 2008)

Top-down vs bottom-up methodologies in multi-agent system design. - Valentino Crespi; Aram Galstyan; Kristina Lerman (Auton. Robots, 2008)

TENTACLES: Self-configuring robotic radio networks in unknown environments. - Harris Chi Ho Chiu; Bo Ryu; Hua Zhu; Pedro A. Szekely; Rajiv T. Maheswaran; Craig Milo Rogers; Aram Galstyan; Behnam Salemi; Michael Rubenstein; Wei-Min Shen (IROS, 2009)

On Maximum a Posteriori Estimation of Hidden Markov Processes. - Armen E. Allahverdyan; Aram Galstyan (UAI, 2009)

Continuous Strategy Replicator Dynamics for Multi-Agent Learning. - Aram Galstyan (CoRR, 2009)

Maximizing Influence Propagation in Networks with Community Structure - Aram Galstyan; Vahe L. Musoyan; Paul R. Cohen (CoRR, 2009)

Community Detection with and without Prior Information - Armen E. Allahverdyan; Aram Galstyan (CoRR, 2009)

Replicator Dynamics of Coevolving Networks. - Aram Galstyan; Ardeshir Kianercy; Armen E. Allahverdyan (AAAI Fall Symposium: Complex Adaptive Systems, 2010)

Co-Evolution of Selection and Influence in Social Networks. - Yoon-Sik Cho; Greg Ver Steeg; Aram Galstyan (AAAI, 2011)

Social Mechanics: An Empirically Grounded Science of Social Media. - Kristina Lerman; Aram Galstyan; Greg Ver Steeg; Tad Hogg (The Future of the Social Web, 2011)

Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs. - Armen E. Allahverdyan; Aram Galstyan (NIPS, 2011)

A Sequence of Relaxation Constraining Hidden Variable Models. - Greg Ver Steeg; Aram Galstyan (UAI, 2011)

Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs (Abstract). - Greg Ver Steeg; Aram Galstyan; Armen E. Allahverdyan (UAI, 2011)

Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs - Aram Galstyan; Greg Ver Steeg; Armen E. Allahverdyan (CoRR, 2011)

A Sequence of Relaxations Constraining Hidden Variable Models - Greg Ver Steeg; Aram Galstyan (CoRR, 2011)

Replicator Dynamics of Co-Evolving Networks - Aram Galstyan; Ardeshir Kianercy; Armen E. Allahverdyan (CoRR, 2011)

Dynamics of Softmax Q-Learning in Two-Player Two-Action Games - Ardeshir Kianercy; Aram Galstyan (CoRR, 2011)

Adaptive agents on evolving networks. - Ardeshir Kianercy; Aram Galstyan; Armen E. Allahverdyan (AAMAS, 2012)

Information transfer in social media. - Greg Ver Steeg; Aram Galstyan (WWW, 2012)

Hidden Markov Models for the Activity Profile of Terrorist Groups - Vasanthan Raghavan; Aram Galstyan; Alexander G. Tartakovsky (CoRR, 2012)

Inferring Predictive Links in Social Media Using Content Transfer - Greg Ver Steeg; Aram Galstyan (CoRR, 2012)

Statistical Tests for Contagion in Observational Social Network Studies. - Greg Ver Steeg; Aram Galstyan (AISTATS, 2013)

Coupled hidden markov models for user activity in social networks. - Vasanthan Raghavan; Greg Ver Steeg; Aram Galstyan; Alexander G. Tartakovsky (ICME Workshops, 2013)

Sentiment Prediction Using Collaborative Filtering. - Jihie Kim; Jae-Bong Yoo; Ho Lim; Huida Qiu; Zornitsa Kozareva; Aram Galstyan (ICWSM, 2013)

Information-theoretic measures of influence based on content dynamics. - Greg Ver Steeg; Aram Galstyan (WSDM, 2013)

Continuous strategy replicator dynamics for multi-agent Q-learning. - Aram Galstyan (Auton. Agents Multi Agent Syst., 2013)

Coevolutionary networks of reinforcement-learning agents. - Ardeshir Kianercy; Aram Galstyan (CoRR, 2013)

Phase Transitions in Community Detection: A Solvable Toy Model. - Greg Ver Steeg; Cristopher Moore; Aram Galstyan; Armen E. Allahverdyan (CoRR, 2013)

Latent Point Process Models for Spatial-Temporal Networks - Yoon-Sik Cho; Aram Galstyan; P. Jeffrey Brantingham; George E. Tita (CoRR, 2013)

Activation Cascades in Structured Populations. - Aram Galstyan (Handbook of Human Computation, 2013)

Where and Why Users "Check In". - Yoon-Sik Cho; Greg Ver Steeg; Aram Galstyan (AAAI, 2014)

Demystifying Information-Theoretic Clustering. - Greg Ver Steeg; Aram Galstyan; Fei Sha; Simon DeDeo (ICML, 2014)

Discovering Structure in High-Dimensional Data Through Correlation Explanation. - Greg Ver Steeg; Aram Galstyan (NIPS, 2014)

Tripartite graph clustering for dynamic sentiment analysis on social media. - Linhong Zhu; Aram Galstyan; James Cheng; Kristina Lerman (SIGMOD Conference, 2014)

Active Inference for Binary Symmetric Hidden Markov Models. - Armen E. Allahverdyan; Aram Galstyan (CoRR, 2014)

Opinion Dynamics with Confirmation Bias. - Armen E. Allahverdyan; Aram Galstyan (CoRR, 2014)

Understanding confounding effects in linguistic coordination: an information-theoretic approach. - Shuyang Gao; Greg Ver Steeg; Aram Galstyan (CoRR, 2014)

Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization. - Linhong Zhu; Greg Ver Steeg; Aram Galstyan (CoRR, 2014)

Modeling Temporal Activity Patterns in Dynamic Social Networks. - Vasanthan Raghavan; Greg Ver Steeg; Aram Galstyan; Alexander G. Tartakovsky (IEEE Trans. Comput. Soc. Syst., 2014)

Mixed Membership Blockmodels for Dynamic Networks with Feedback. - Yoon-Sik Cho; Greg Ver Steeg; Aram Galstyan (Handbook of Mixed Membership Models and Their Applications, 2014)

Efficient Estimation of Mutual Information for Strongly Dependent Variables. - Shuyang Gao; Greg Ver Steeg; Aram Galstyan (AISTATS, 2015)

Maximally Informative Hierarchical Representations of High-Dimensional Data. - Greg Ver Steeg; Aram Galstyan (AISTATS, 2015)

Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly. - Sarah K. Madsen; Greg Ver Steeg; Adam Mezher; Neda Jahanshad; Talia M. Nir; Xue Hua; Boris A. Gutman; Aram Galstyan; Paul M. Thompson (ISBI, 2015)

Information-Theoretic Clustering of Neuroimaging Metrics Related to Cognitive Decline in the Elderly. - Madelaine Daianu; Greg Ver Steeg; Adam Mezher; Neda Jahanshad; Talia M. Nir; Xiaoran Yan; Gautam Prasad; Kristina Lerman; Aram Galstyan; Paul M. Thompson (MCV@MICCAI, 2015)

Estimating Mutual Information by Local Gaussian Approximation. - Shuyang Gao; Greg Ver Steeg; Aram Galstyan (UAI, 2015)

Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text. - Sahil Garg; Aram Galstyan; Ulf Hermjakob; Daniel Marcu (AAAI, 2016)

Modeling Concept Dependencies in a Scientific Corpus. - Jonathan Gordon 001; Linhong Zhu; Aram Galstyan; Prem Natarajan; Gully Burns (ACL (1), 2016)

The Information Sieve. - Greg Ver Steeg; Aram Galstyan (ICML, 2016)

Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly. - Sarah K. Madsen; Greg Ver Steeg; Madelaine Daianu; Adam Mezher; Neda Jahanshad; Talia M. Nir; Xue Hua; Boris A. Gutman; Aram Galstyan; Paul M. Thompson (Image Processing, 2016)

Variational Information Maximization for Feature Selection. - Shuyang Gao; Greg Ver Steeg; Aram Galstyan (NIPS, 2016)

Unsupervised Entity Resolution on Multi-type Graphs. - Linhong Zhu; Majid Ghasemi-Gol; Pedro A. Szekely; Aram Galstyan; Craig A. Knoblock (ISWC (1), 2016)

Predicting Online Extremism, Content Adopters, and Interaction Reciprocity. - Emilio Ferrara; Wen-Qiang Wang; Onur Varol; Alessandro Flammini; Aram Galstyan (SocInfo (2), 2016)

Latent Space Model for Multi-Modal Social Data. - Yoon-Sik Cho; Greg Ver Steeg; Emilio Ferrara; Aram Galstyan (WWW, 2016)

The DARPA Twitter Bot Challenge. - V. S. Subrahmanian; Amos Azaria; Skylar Durst; Vadim Kagan; Aram Galstyan; Kristina Lerman; Linhong Zhu; Emilio Ferrara; Alessandro Flammini; Filippo Menczer (Computer, 2016)

Toward Interpretable Topic Discovery via Anchored Correlation Explanation. - Kyle Reing; David C. Kale; Greg Ver Steeg; Aram Galstyan (CoRR, 2016)

The DARPA Twitter Bot Challenge. - V. S. Subrahmanian; Amos Azaria; Skylar Durst; Vadim Kagan; Aram Galstyan; Kristina Lerman; Linhong Zhu; Emilio Ferrara; Alessandro Flammini; Filippo Menczer; Rand Waltzman; Andrew Stevens; et al. (CoRR, 2016)

Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks. - Linhong Zhu; Dong Guo; Junming Yin; Greg Ver Steeg; Aram Galstyan (IEEE Trans. Knowl. Data Eng., 2016)

Disentangled representations via synergy minimization. - Greg Ver Steeg; Rob Brekelmans; Hrayr Harutyunyan; Aram Galstyan (Allerton, 2017)

Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (Extended Abstract). - Linhong Zhu; Dong Guo; Junming Yin; Greg Ver Steeg; Aram Galstyan (ICDE, 2017)

Sifting Common Information from Many Variables. - Greg Ver Steeg; Shuyang Gao; Kyle Reing; Aram Galstyan (IJCAI, 2017)

Multitask Learning and Benchmarking with Clinical Time Series Data. - Hrayr Harutyunyan; Hrant Khachatrian; David C. Kale; Aram Galstyan (CoRR, 2017)

Low Complexity Gaussian Latent Factor Models and a Blessing of Dimensionality. - Greg Ver Steeg; Aram Galstyan (CoRR, 2017)

Unifying Local and Global Change Detection in Dynamic Networks. - Wenzhe Li; Dong Guo; Greg Ver Steeg; Aram Galstyan (CoRR, 2017)

Emergence of Leadership in Communication. - Armen E. Allahverdyan; Aram Galstyan (CoRR, 2017)

Efficient Representation for Natural Language Processing via Kernelized Hashcodes. - Sahil Garg; Aram Galstyan; Irina Rish; Guillermo A. Cecchi; Shuyang Gao (CoRR, 2017)

Memory-induced mechanism for self-sustaining activity in networks. - Armen E. Allahverdyan; Greg Ver Steeg; Aram Galstyan (CoRR, 2017)

Mining and Forecasting Career Trajectories of Music Artists. - Shushan Arakelyan; Fred Morstatter; Margaret Martin; Emilio Ferrara; Aram Galstyan (HT, 2018)

Embedding Networks with Edge Attributes. - Palash Goyal; Homa Hosseinmardi; Emilio Ferrara; Aram Galstyan (HT, 2018)

Dialogue Modeling Via Hash Functions. - Sahil Garg; Guillermo A. Cecchi; Irina Rish; Shuyang Gao; Greg Ver Steeg; Sarik Ghazarian; Palash Goyal; Aram Galstyan (LaCATODA@IJCAI, 2018)

Invariant Representations without Adversarial Training. - Daniel Moyer; Shuyang Gao; Rob Brekelmans; Aram Galstyan; Greg Ver Steeg (NeurIPS, 2018)

A Forest Mixture Bound for Block-Free Parallel Inference. - Neal Lawton; Greg Ver Steeg; Aram Galstyan (UAI, 2018)

From Alt-Right to Alt-Rechts: Twitter Analysis of the 2017 German Federal Election. - Fred Morstatter; Yunqiu Shao; Aram Galstyan; Shanika Karunasekera (WWW (Companion Volume), 2018)

Stochastic Learning of Nonstationary Kernels for Natural Language Modeling. - Sahil Garg; Greg Ver Steeg; Aram Galstyan (CoRR, 2018)

Adaptive prior probabilities via optimization of risk and entropy. - Armen E. Allahverdyan; Aram Galstyan; Ali E. Abbas; Zbigniew R. Struzik (CoRR, 2018)

Evading the Adversary in Invariant Representation. - Daniel Moyer; Shuyang Gao; Rob Brekelmans; Greg Ver Steeg; Aram Galstyan (CoRR, 2018)

Adaptive decision making via entropy minimization. - Armen E. Allahverdyan; Aram Galstyan; Ali E. Abbas; Zbigniew R. Struzik (Int. J. Approx. Reason., 2018)

Capturing Edge Attributes via Network Embedding. - Palash Goyal; Homa Hosseinmardi; Emilio Ferrara; Aram Galstyan (IEEE Trans. Comput. Soc. Syst., 2018)

Kernelized Hashcode Representations for Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Irina Rish; Guillermo A. Cecchi; Shuyang Gao (AAAI, 2019)

Auto-Encoding Total Correlation Explanation. - Shuyang Gao; Rob Brekelmans; Greg Ver Steeg; Aram Galstyan (AISTATS, 2019)

Debiasing community detection: the importance of lowly connected nodes. - Ninareh Mehrabi; Fred Morstatter; Nanyun Peng 001; Aram Galstyan (ASONAM, 2019)

BioRelEx 1.0: Biological Relation Extraction Benchmark. - Hrant Khachatrian; Lilit Nersisyan; Karen Hambardzumyan; Tigran Galstyan; Anna Hakobyan; Arsen Arakelyan; Andrey Rzhetsky; Aram Galstyan (BioNLP@ACL, 2019)

Deep Structured Neural Network for Event Temporal Relation Extraction. - Rujun Han; I-Hung Hsu; Mu Yang; Aram Galstyan; Ralph M. Weischedel; Nanyun Peng 001 (CoNLL, 2019)

Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Guillermo A. Cecchi (EMNLP/IJCNLP (1), 2019)

MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing. - Sami Abu-El-Haija; Bryan Perozzi; Amol Kapoor; Nazanin Alipourfard; Kristina Lerman; Hrayr Harutyunyan; Greg Ver Steeg; Aram Galstyan (ICML, 2019)

SAGE: A Hybrid Geopolitical Event Forecasting System. - Fred Morstatter; Aram Galstyan; Gleb Satyukov; Daniel Benjamin; Andrés Abeliuk; Mehrnoosh Mirtaheri; K. S. M. Tozammel Hossain; Pedro A. Szekely; Emilio Ferrara; Akira Matsui; Mark Steyvers; Stephen Bennett; et al. (IJCAI, 2019)

Exact Rate-Distortion in Autoencoders via Echo Noise. - Rob Brekelmans; Daniel Moyer; Aram Galstyan; Greg Ver Steeg (NeurIPS, 2019)

Fast structure learning with modular regularization. - Greg Ver Steeg; Hrayr Harutyunyan; Daniel Moyer; Aram Galstyan (NeurIPS, 2019)

Coupled Clustering of Time-Series and Networks. - Yike Liu; Linhong Zhu; Pedro A. Szekely; Aram Galstyan; Danai Koutra (SDM, 2019)

Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings. - Sarik Ghazarian; Johnny Tian-Zheng Wei; Aram Galstyan; Nanyun Peng 001 (CoRR, 2019)

Efficient Covariance Estimation from Temporal Data. - Hrayr Harutyunyan; Daniel Moyer; Hrant Khachatrian; Greg Ver Steeg; Aram Galstyan (CoRR, 2019)

Nearly-Unsupervised Hashcode Representations for Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Guillermo A. Cecchi (CoRR, 2019)

Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. - Sahil Garg; Irina Rish; Guillermo A. Cecchi; Palash Goyal; Sarik Ghazarian; Shuyang Gao; Greg Ver Steeg; Aram Galstyan (AAAI, 2020)

Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems. - Sarik Ghazarian; Ralph M. Weischedel; Aram Galstyan; Nanyun Peng 001 (AAAI, 2020)

Anchor Attention for Hybrid Crowd Forecasts Aggregation. - Yuzhong Huang; Andrés Abeliuk; Fred Morstatter; Pavel Atanasov; Aram Galstyan (AAMAS, 2020)

Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity Recognition. - Ninareh Mehrabi; Thamme Gowda; Fred Morstatter; Nanyun Peng 001; Aram Galstyan (HT, 2020)

All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference. - Rob Brekelmans; Vaden Masrani; Frank Wood; Greg Ver Steeg; Aram Galstyan (ICML, 2020)

Improving generalization by controlling label-noise information in neural network weights. - Hrayr Harutyunyan; Kyle Reing; Greg Ver Steeg; Aram Galstyan (ICML, 2020)

Graph Embedding with Personalized Context Distribution. - Di Huang; Zihao He; Yuzhong Huang; Kexuan Sun 002; Sami Abu-El-Haija; Bryan Perozzi; Kristina Lerman; Fred Morstatter; Aram Galstyan (WWW (Companion Volume), 2020)

Towards Learning Representations of Binary Executable Files for Security Tasks. - Shushan Arakelyan; Christophe Hauser; Erik Kline; Aram Galstyan (CoRR, 2020)

Event Cartography: Latent Point Process Embeddings. - Myrl G. Marmarelis; Greg Ver Steeg; Aram Galstyan (CoRR, 2020)

Sequential Unsupervised Domain Adaptation through Prototypical Distributions. - Mohammad Rostami; Aram Galstyan (CoRR, 2020)

Robust Classification under Class-Dependent Domain Shift. - Tigran Galstyan; Hrant Khachatrian; Greg Ver Steeg; Aram Galstyan (CoRR, 2020)

Compressing Deep Neural Networks via Layer Fusion. - James O'Neill; Greg Ver Steeg; Aram Galstyan (CoRR, 2020)

Leveraging Clickstream Trajectories to Reveal Low-Quality Workers in Crowdsourced Forecasting Platforms. - Akira Matsui; Emilio Ferrara; Fred Morstatter; Andrés Abeliuk; Aram Galstyan (CoRR, 2020)

Annealed Importance Sampling with q-Paths. - Rob Brekelmans; Vaden Masrani; Thang Bui; Frank Wood; Aram Galstyan; Greg Ver Steeg; Frank Nielsen (CoRR, 2020)

Likelihood Ratio Exponential Families. - Rob Brekelmans; Frank Nielsen; Alireza Makhzani; Aram Galstyan; Greg Ver Steeg (CoRR, 2020)

Stacking models for nearly optimal link prediction in complex networks. - Amir Ghasemian; Homa Hosseinmardi; Aram Galstyan; Edoardo M. Airoldi; Aaron Clauset (Proc. Natl. Acad. Sci. USA, 2020)

Maximizing Multivariate Information With Error-Correcting Codes. - Kyle Reing; Greg Ver Steeg; Aram Galstyan (IEEE Trans. Inf. Theory, 2020)

Exacerbating Algorithmic Bias through Fairness Attacks. - Ninareh Mehrabi; Muhammad Naveed; Fred Morstatter; Aram Galstyan (AAAI, 2021)

ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data. - Woojeong Jin 001; Rahul Khanna; Suji Kim; Dong-Ho Lee; Fred Morstatter; Aram Galstyan; Xiang Ren 001 (ACL/IJCNLP (1), 2021)

Layer-Wise Neural Network Compression via Layer Fusion. - James O'Neill; Greg Ver Steeg; Aram Galstyan (ACML, 2021)

Influence Decompositions For Neural Network Attribution. - Kyle Reing; Greg Ver Steeg; Aram Galstyan (AISTATS, 2021)

One-shot Learning for Temporal Knowledge Graphs. - Mehrnoosh Mirtaheri; Mohammad Rostami; Xiang Ren 001; Fred Morstatter; Aram Galstyan (AKBC, 2021)

Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. - Ninareh Mehrabi; Pei Zhou; Fred Morstatter; Jay Pujara; Xiang Ren 001; Aram Galstyan (EMNLP (1), 2021)

Partner-Assisted Learning for Few-Shot Image Classification. - Jiawei Ma; Hanchen Xie; Guangxing Han; Shih-Fu Chang; Aram Galstyan; Wael Abd-Almageed (ICCV, 2021)

Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning. - Elan Sopher Markowitz; Keshav Balasubramanian; Mehrnoosh Mirtaheri; Sami Abu-El-Haija; Bryan Perozzi; Greg Ver Steeg; Aram Galstyan (ICLR, 2021)

DiSCoL: Toward Engaging Dialogue Systems through Conversational Line Guided Response Generation. - Sarik Ghazarian; Zixi Liu; Tuhin Chakrabarty; Xuezhe Ma; Aram Galstyan; Nanyun Peng 001 (NAACL-HLT (Demonstrations), 2021)

Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation. - Sarik Ghazarian; Zixi Liu; Akash SM; Ralph M. Weischedel; Aram Galstyan; Nanyun Peng 001 (NAACL-HLT, 2021)

Implicit SVD for Graph Representation Learning. - Sami Abu-El-Haija; Hesham Mostafa; Marcel Nassar; Valentino Crespi; Greg Ver Steeg; Aram Galstyan (NeurIPS, 2021)

Information-theoretic generalization bounds for black-box learning algorithms. - Hrayr Harutyunyan; Maxim Raginsky; Greg Ver Steeg; Aram Galstyan (NeurIPS, 2021)

Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling. - Greg Ver Steeg; Aram Galstyan (NeurIPS, 2021)

q-Paths: Generalizing the geometric annealing path using power means. - Vaden Masrani; Rob Brekelmans; Thang Bui; Frank Nielsen; Aram Galstyan; Greg Ver Steeg; Frank Wood (UAI, 2021)

MUSCLE: Strengthening Semi-Supervised Learning Via Concurrent Unsupervised Learning Using Mutual Information Maximization. - Hanchen Xie; Mohamed E. Hussein 001; Aram Galstyan; Wael Abd-Almageed (WACV, 2021)

Fast Graph Learning with Unique Optimal Solutions. - Sami Abu-El-Haija; Valentino Crespi; Greg Ver Steeg; Aram Galstyan (CoRR, 2021)

Identifying botnet IP address clusters using natural language processing techniques on honeypot command logs. - Valentino Crespi; Wes Hardaker; Sami Abu-El-Haija; Aram Galstyan (CoRR, 2021)

Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation. - Mohammad Rostami; Aram Galstyan (CoRR, 2021)

Attributing Fair Decisions with Attention Interventions. - Ninareh Mehrabi; Umang Gupta; Fred Morstatter; Greg Ver Steeg; Aram Galstyan (CoRR, 2021)

Bin2vec: learning representations of binary executable programs for security tasks. - Shushan Arakelyan; Sima Arasteh; Christophe Hauser; Erik Kline; Aram Galstyan (Cybersecur., 2021)

Discovering Higher-Order Interactions Through Neural Information Decomposition. - Kyle Reing; Greg Ver Steeg; Aram Galstyan (Entropy, 2021)

Identifying and Analyzing Cryptocurrency Manipulations in Social Media. - Mehrnoosh Mirtaheri; Sami Abu-El-Haija; Fred Morstatter; Greg Ver Steeg; Aram Galstyan (IEEE Trans. Comput. Soc. Syst., 2021)

On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations. - Yang Trista Cao; Yada Pruksachatkun; Kai-Wei Chang; Rahul Gupta 001; Varun Kumar; Jwala Dhamala; Aram Galstyan (ACL (2), 2022)

DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations. - Sarik Ghazarian; Nuan Wen; Aram Galstyan; Nanyun Peng 001 (ACL (1), 2022)

Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. - Umang Gupta; Jwala Dhamala; Varun Kumar; Apurv Verma; Yada Pruksachatkun; Satyapriya Krishna; Rahul Gupta 001; Kai-Wei Chang; Greg Ver Steeg; Aram Galstyan (ACL (Findings), 2022)

Failure Modes of Domain Generalization Algorithms. - Tigran Galstyan; Hrayr Harutyunyan; Hrant Khachatrian; Greg Ver Steeg; Aram Galstyan (CVPR, 2022)

Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations. - Kuan-Hao Huang; Varun Iyer; Anoop Kumar; Sriram Venkatapathy; Kai-Wei Chang; Aram Galstyan (EMNLP (Findings), 2022)

Learning Under Label Noise for Robust Spoken Language Understanding systems. - Anoop Kumar; Pankaj Kumar Sharma; Aravind Illa; Sriram Venkatapathy; Subhrangshu Nandi; Pritam Varma; Anurag Dwarakanath; Aram Galstyan (INTERSPEECH, 2022)

Formal limitations of sample-wise information-theoretic generalization bounds. - Hrayr Harutyunyan; Greg Ver Steeg; Aram Galstyan (ITW, 2022)

Temporal Generalization for Spoken Language Understanding. - Judith Gaspers; Anoop Kumar; Greg Ver Steeg; Aram Galstyan (NAACL-HLT (Industry Papers), 2022)

StATIK: Structure and Text for Inductive Knowledge Graph Completion. - Elan Markowitz; Keshav Balasubramanian; Mehrnoosh Mirtaheri; Murali Annavaram; Aram Galstyan; Greg Ver Steeg (NAACL-HLT (Findings), 2022)

Robust Conversational Agents against Imperceptible Toxicity Triggers. - Ninareh Mehrabi; Ahmad Beirami; Fred Morstatter; Aram Galstyan (NAACL-HLT, 2022)

An Analysis of The Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation. - Jwala Dhamala; Varun Kumar; Rahul Gupta 001; Kai-Wei Chang; Aram Galstyan (SLT, 2022)

Inferring topological transitions in pattern-forming processes with self-supervised learning. - Marcin Abram; Keith Burghardt; Greg Ver Steeg; Aram Galstyan; Rémi Dingreville (CoRR, 2022)

Bounding the Effects of Continuous Treatments for Hidden Confounders. - Myrl G. Marmarelis; Greg Ver Steeg; Aram Galstyan (CoRR, 2022)

Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models. - Ninareh Mehrabi; Palash Goyal; Apurv Verma; Jwala Dhamala; Varun Kumar; Qian Hu; Kai-Wei Chang; Richard S. Zemel; Aram Galstyan; Rahul Gupta 001 (CoRR, 2022)

A Survey on Bias and Fairness in Machine Learning. - Ninareh Mehrabi; Fred Morstatter; Nripsuta Saxena; Kristina Lerman; Aram Galstyan (ACM Comput. Surv., 2022)

Identifying geopolitical event precursors using attention-based LSTMs. - K. S. M. Tozammel Hossain; Hrayr Harutyunyan; Yue Ning 001; Brendan Kennedy 001; Naren Ramakrishnan; Aram Galstyan (Frontiers Artif. Intell., 2022)

A Metric Space for Point Process Excitations. - Myrl G. Marmarelis; Greg Ver Steeg; Aram Galstyan (J. Artif. Intell. Res., 2022)

Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distributions. - Mohammad Rostami; Aram Galstyan (AAAI, 2023)

Measuring and Mitigating Local Instability in Deep Neural Networks. - Arghya Datta; Subhrangshu Nandi; Jingcheng Xu; Greg Ver Steeg; He Xie; Anoop Kumar; Aram Galstyan (ACL (Findings), 2023)

ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems. - Sarik Ghazarian; Yijia Shao; Rujun Han; Aram Galstyan; Nanyun Peng 001 (ACL (1), 2023)

Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning. - Umang Gupta; Aram Galstyan; Greg Ver Steeg (ACL (Findings), 2023)

ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation. - Kuan-Hao Huang; Varun Iyer; I-Hung Hsu; Anoop Kumar; Kai-Wei Chang; Aram Galstyan (ACL (1), 2023)

Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs. - Abishek Komma; Nagesh Panyam Chandrasekarasastry; Timothy Leffel; Anuj Goyal; Angeliki Metallinou; Spyros Matsoukas; Aram Galstyan (ACL (industry), 2023)

Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models. - Neal Lawton; Anoop Kumar; Govind Thattai; Aram Galstyan; Greg Ver Steeg (ACL (Findings), 2023)

Resolving Ambiguities in Text-to-Image Generative Models. - Ninareh Mehrabi; Palash Goyal; Apurv Verma; Jwala Dhamala; Varun Kumar; Qian Hu; Kai-Wei Chang; Richard S. Zemel; Aram Galstyan; Rahul Gupta 001 (ACL (1), 2023)

History repeats: Overcoming catastrophic forgetting for event-centric temporal knowledge graph completion. - Mehrnoosh Mirtaheri; Mohammad Rostami; Aram Galstyan (ACL (Findings), 2023)

The First Workshop on Personalized Generative AI @ CIKM 2023: Personalization Meets Large Language Models. - Zheng Chen 010; Ziyan Jiang; Fan Yang; Zhankui He; Yupeng Hou; Eunah Cho; Julian J. McAuley; Aram Galstyan; Xiaohua Hu 001; Jie Yang 028 (CIKM, 2023)

StATIK+: Structure and Text for Inductive Knowledge Graph Modeling and Paths towards Enterprise Implementations. - Elan Sopher Markowitz; Aram Galstyan (EKG-LLM@CIKM, 2023)

Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding. - Zheng Chen 010; Ziyan Jiang; Fan Yang; Eunah Cho; Xing Fan; Xiaojiang Huang; Yanbin Lu; Aram Galstyan (EMNLP (Industry Track), 2023)

Domain Adaptation for Sentiment Analysis Using Robust Internal Representations. - Mohammad Rostami; Digbalay Bose; Shrikanth Narayanan; Aram Galstyan (EMNLP (Findings), 2023)

"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. - Anaelia Ovalle; Palash Goyal; Jwala Dhamala; Zachary Jaggers; Kai-Wei Chang; Aram Galstyan; Richard S. Zemel; Rahul Gupta 001 (FAccT, 2023)

Cognitively Inspired Learning of Incremental Drifting Concepts. - Mohammad Rostami; Aram Galstyan (IJCAI, 2023)

Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. - Elizabeth Haddad; Myrl G. Marmarelis; Talia M. Nir; Aram Galstyan; Greg Ver Steeg; Neda Jahanshad (MLCN@MICCAI, 2023)

Partial identification of dose responses with hidden confounders. - Myrl G. Marmarelis; Elizabeth Haddad; Andrew Jesson; Neda Jahanshad; Aram Galstyan; Greg Ver Steeg (UAI, 2023)

Incorporating Fairness in Large Scale NLU Systems. - Rahul Gupta 001; Lisa Bauer; Kai-Wei Chang; Jwala Dhamala; Aram Galstyan; Palash Goyal; Qian Hu; Avni Khatri; Rohit Parimi; Charith Peris; Apurv Verma; Richard S. Zemel; et al. (WSDM, 2023)

Multi-Task Knowledge Enhancement for Zero-Shot and Multi-Domain Recommendation in an AI Assistant Application. - Elan Markowitz; Ziyan Jiang; Fan Yang; Xing Fan; Tony Chen; Greg Ver Steeg; Aram Galstyan (CoRR, 2023)

Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding. - Myrl G. Marmarelis; Greg Ver Steeg; Aram Galstyan; Fred Morstatter (CoRR, 2023)

JAB: Joint Adversarial Prompting and Belief Augmentation. - Ninareh Mehrabi; Palash Goyal; Anil Ramakrishna; Jwala Dhamala; Shalini Ghosh; Richard S. Zemel; Kai-Wei Chang; Aram Galstyan; Rahul Gupta 001 (CoRR, 2023)

Are you talking to ['xem'] or ['x', 'em']? On Tokenization and Addressing Misgendering in LLMs with Pronoun Tokenization Parity. - Anaelia Ovalle; Ninareh Mehrabi; Palash Goyal; Jwala Dhamala; Kai-Wei Chang; Richard S. Zemel; Aram Galstyan; Rahul Gupta 001 (CoRR, 2023)

Hybrid forecasting of geopolitical events†. - Daniel M. Benjamin; Fred Morstatter; Ali E. Abbas; Andrés Abeliuk; Pavel Atanasov; Stephen Bennett; Andreas Beger; Saurabh Birari; David V. Budescu; Michele Catasta; Emilio Ferrara; Lucas Haravitch; et al. (AI Mag., 2023)

Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. - Elan Markowitz; Anil Ramakrishna; Jwala Dhamala; Ninareh Mehrabi; Charith Peris; Rahul Gupta 001; Kai-Wei Chang; Aram Galstyan (ACL (1), 2024)

Contrastive Instruction Tuning. - Tianyi Yan; Fei Wang 060; James Y. Huang; Wenxuan Zhou; Fan Yin; Aram Galstyan; Wenpeng Yin 001; Muhao Chen 001 (ACL (Findings), 2024)

Policy Learning for Localized Interventions from Observational Data. - Myrl G. Marmarelis; Fred Morstatter; Aram Galstyan; Greg Ver Steeg (AISTATS, 2024)

Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding. - Myrl G. Marmarelis; Greg Ver Steeg; Aram Galstyan; Fred Morstatter (CLeaR, 2024)

Agenda-Driven Question Generation: A Case Study in the Courtroom Domain. - Yi Ren Fung 001; Anoop Kumar; Aram Galstyan; Heng Ji 001; Prem Natarajan (LREC/COLING, 2024)

Correcting Language Model Outputs by Editing Salient Layers. - Kshitij Mishra; Tamer Soliman; Anil Ramakrishna; Aram Galstyan; Anoop Kumar (EACL (Findings), 2024)

Prompt Perturbation Consistency Learning for Robust Language Models. - Yao Qiang; Subhrangshu Nandi; Ninareh Mehrabi; Greg Ver Steeg; Anoop Kumar; Anna Rumshisky; Aram Galstyan (EACL (Findings), 2024)

FLIRT: Feedback Loop In-context Red Teaming. - Ninareh Mehrabi; Palash Goyal; Christophe Dupuy; Qian Hu; Shalini Ghosh; Richard S. Zemel; Kai-Wei Chang; Aram Galstyan; Rahul Gupta 001 (EMNLP, 2024)

Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification. - Tao Meng; Ninareh Mehrabi; Palash Goyal; Anil Ramakrishna; Aram Galstyan; Richard S. Zemel; Kai-Wei Chang; Rahul Gupta 001; Charith Peris (EMNLP (Findings), 2024)

Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models. - Fei Wang 060; Ninareh Mehrabi; Palash Goyal; Rahul Gupta 001; Kai-Wei Chang; Aram Galstyan (EMNLP, 2024)

QuAILoRA: Quantization-Aware Initialization for LoRA. - Neal Lawton; Aishwarya Padmakumar; Judith Gaspers; Jack FitzGerald; Anoop Kumar; Greg Ver Steeg; Aram Galstyan (ENLSP, 2024)

Leveraging LLMs for Dialogue Quality Measurement. - Jinghan Jia; Abi Komma; Timothy Leffel; Xujun Peng; Ajay Nagesh; Tamer Soliman; Aram Galstyan; Anoop Kumar (NAACL (Industry Track), 2024)

The steerability of large language models toward data-driven personas. - Junyi Li; Charith Peris; Ninareh Mehrabi; Palash Goyal; Kai-Wei Chang; Aram Galstyan; Richard S. Zemel; Rahul Gupta 001 (NAACL-HLT, 2024)

Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies. - Anaelia Ovalle; Ninareh Mehrabi; Palash Goyal; Jwala Dhamala; Kai-Wei Chang; Richard S. Zemel; Aram Galstyan; Yuval Pinter; Rahul Gupta 001 (NAACL-HLT (Findings), 2024)

MICo: Preventative Detoxification of Large Language Models through Inhibition Control. - Roy Siegelmann; Ninareh Mehrabi; Palash Goyal; Prasoon Goyal; Lisa Bauer; Jwala Dhamala; Aram Galstyan; Rahul Gupta 001; Reza Ghanadan (NAACL-HLT (Findings), 2024)

SeRA: Self-Reviewing and Alignment of Large Language Models using Implicit Reward Margins. - Jongwoo Ko; Saket Dingliwal; Bhavana Ganesh; Sailik Sengupta; Sravan Bodapati; Aram Galstyan (CoRR, 2024)

Adaptive Video Understanding Agent: Enhancing efficiency with dynamic frame sampling and feedback-driven reasoning. - Sullam Jeoung; Goeric Huybrechts; Bhavana Ganesh; Aram Galstyan; Sravan Bodapati (CoRR, 2024)

Learning Morphisms with Gauss-Newton Approximation for Growing Networks. - Neal Lawton; Aram Galstyan; Greg Ver Steeg (CoRR, 2024)

Hybrid Forecasting of Geopolitical Events. - Daniel M. Benjamin; Fred Morstatter; Ali E. Abbas; Andrés Abeliuk; Pavel Atanasov; Stephen Bennett; Andreas Beger; Saurabh Birari; David V. Budescu; Michele Catasta; Emilio Ferrara; Lucas Haravitch; et al. (CoRR, 2024)

Towards Safety Reasoning in LLMs: AI-agentic Deliberation for Policy-embedded CoT Data Creation. - Tharindu Kumarage; Ninareh Mehrabi; Anil Ramakrishna; Xinyan Zhao; Richard S. Zemel; Kai-Wei Chang; Aram Galstyan; Rahul Gupta 001; Charith Peris (ACL (Findings), 2025)

Wanda++: Pruning Large Language Models via Regional Gradients. - Yifan Yang; Kai Zhen; Bhavana Ganesh; Aram Galstyan; Goeric Huybrechts; Markus Müller; Jonas M. Kübler; Rupak Vignesh Swaminathan; Athanasios Mouchtaris; Sravan Babu Bodapati; Nathan Susanj; Zheng Zhang; et al. (ACL (Findings), 2025)

Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application. - Elan Markowitz; Ziyan Jiang; Fan Yang; Xing Fan; Zheng Chen 010; Greg Ver Steeg; Aram Galstyan (ICASSP, 2025)

SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins. - Jongwoo Ko; Saket Dingliwal; Bhavana Ganesh; Sailik Sengupta; Sravan Babu Bodapati; Aram Galstyan (ICLR, 2025)

On Localizing and Deleting Toxic Memories in Large Language Models. - Anubrata Das 001; Manoj Kumar 007; Ninareh Mehrabi; Anil Ramakrishna; Anna Rumshisky; Kai-Wei Chang; Aram Galstyan; Morteza Ziyadi; Rahul Gupta 001 (NAACL (Findings), 2025)

Making Sense Of Distributed Representations With Activation Spectroscopy. - Kyle Reing; Greg Ver Steeg; Aram Galstyan (CoRR, 2025)

K-Edit: Language Model Editing with Contextual Knowledge Awareness. - Elan Markowitz; Anil Ramakrishna; Ninareh Mehrabi; Charith Peris; Rahul Gupta 001; Kai-Wei Chang; Aram Galstyan (CoRR, 2025)

KG-LLM-Bench: A Scalable Benchmark for Evaluating LLM Reasoning on Textualized Knowledge Graphs. - Elan Markowitz; Krupa Galiya; Greg Ver Steeg; Aram Galstyan (CoRR, 2025)

Mamba Drafters for Speculative Decoding. - Daewon Choi; Seunghyuk Oh; Saket Dingliwal; Jihoon Tack; Kyuyoung Kim; Woomin Song; Seojin Kim; Insu Han; Jinwoo Shin; Aram Galstyan; Shubham Katiyar; Sravan Babu Bodapati (CoRR, 2025)

Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers. - Woomin Song; Sai Muralidhar Jayanthi; Srikanth Ronanki; Kanthashree Mysore Sathyendra; Jinwoo Shin; Aram Galstyan; Shubham Katiyar; Sravan Babu Bodapati (CoRR, 2025)

Accelerated Test-Time Scaling with Model-Free Speculative Sampling. - Woomin Song; Saket Dingliwal; Sai Muralidhar Jayanthi; Bhavana Ganesh; Jinwoo Shin; Aram Galstyan; Sravan Babu Bodapati (CoRR, 2025)

The Amazon Nova Family of Models: Technical Report and Model Card. - Amazon AGI; Aaron Langford; Aayush Shah; Abhanshu Gupta; Abhimanyu Bhatter; Abhinav Goyal 004; Abhinav Mathur; Abhinav Mohanty; Abhishek Kumar; Abhishek Sethi; Abi Komma; Abner Pena; et al. (CoRR, 2025)

Kaleidoscopic Teaming in Multi Agent Simulations. - Ninareh Mehrabi; Tharindu Kumarage; Kai-Wei Chang; Aram Galstyan; Rahul Gupta 001 (CoRR, 2025)

Think Clearly: Improving Reasoning via Redundant Token Pruning. - Daewon Choi; Jimin Lee; Jihoon Tack; Woomin Song; Saket Dingliwal; Sai Muralidhar Jayanthi; Bhavana Ganesh; Jinwoo Shin; Aram Galstyan; Sravan Babu Bodapati (CoRR, 2025)