An Interactive Web Based Spatio-Temporal Visualization System. - Anil Ramakrishna; Yu-Han Chang; Rajiv T. Maheswaran (ISVC (2), 2013)

A quantitative analysis of gender differences in movies using psycholinguistic normatives. - Anil Ramakrishna; Nikolaos Malandrakis; Elizabeth Staruk; Shrikanth S. Narayanan (EMNLP, 2015)

On quantifying facial expression-related atypicality of children with Autism Spectrum Disorder. - Tanaya Guha; Zhaojun Yang; Anil Ramakrishna; Ruth B. Grossman; Darren Hedley; Sungbok Lee; Shrikanth S. Narayanan (ICASSP, 2015)

Acoustic-prosodic correlates of 'awkward' prosody in story retellings from adolescents with autism. - Daniel Bone; Matthew P. Black; Anil Ramakrishna; Ruth B. Grossman; Shrikanth S. Narayanan (INTERSPEECH, 2015)

Hierarchical Active Transfer Learning. - David C. Kale; Marjan Ghazvininejad; Anil Ramakrishna; Jingrui He; Yan Liu 002 (SDM, 2015)

An Expectation Maximization Approach to Joint Modeling of Multidimensional Ratings Derived from Multiple Annotators. - Anil Ramakrishna; Rahul Gupta 001; Ruth B. Grossman; Shrikanth S. Narayanan (INTERSPEECH, 2016)

Linguistic analysis of differences in portrayal of movie characters. - Anil Ramakrishna; Victor R. Martinez; Nikolaos Malandrakis; Karan Singla; Shrikanth S. Narayanan (ACL (1), 2017)

Computational Modeling of Conversational Humor in Psychotherapy. - Anil Ramakrishna; Timothy Greer; David C. Atkins; Shrikanth S. Narayanan (INTERSPEECH, 2018)

The ELISA Situation Frame extraction for low resource languages pipeline for LoReHLT'2016. - Nikolaos Malandrakis; Anil Ramakrishna; Victor R. Martinez; Tanner Sorensen; Dogan Can; Shrikanth S. Narayanan (Mach. Transl., 2018)

Violence Rating Prediction from Movie Scripts. - Victor R. Martinez; Krishna Somandepalli; Karan Singla; Anil Ramakrishna; Yalda T. Uhls; Shrikanth S. Narayanan (AAAI, 2019)

A system for the 2019 Sentiment, Emotion and Cognitive State Task of DARPA's LORELEI project. - Victor R. Martinez; Anil Ramakrishna; Ming-Chang Chiu; Karan Singla; Shrikanth S. Narayanan (ACII, 2019)

A system for the 2019 Sentiment, Emotion and Cognitive State Task of DARPAs LORELEI project. - Victor R. Martinez; Anil Ramakrishna; Ming-Chang Chiu; Karan Singla; Shrikanth S. Narayanan (CoRR, 2019)

Sentence Level Estimation of Psycholinguistic Norms Using Joint Multidimensional Annotations. - Anil Ramakrishna; Shrikanth Narayanan (INTERSPEECH, 2020)

Victim or Perpetrator? Analysis of Violent Characters Portrayals from Movie Scripts. - Victor R. Martinez; Krishna Somandepalli; Karan Singla; Anil Ramakrishna; Yalda T. Uhls; Shrikanth Narayanan (CoRR, 2020)

Towards Realistic Single-Task Continuous Learning Research for NER. - Justin Payan; Yuval Merhav; He Xie; Satyapriya Krishna; Anil Ramakrishna; Mukund Sridhar; Rahul Gupta 001 (EMNLP (Findings), 2021)

Improving Large-Scale Conversational Assistants using Model Interpretation based Training Sample Selection. - Stefan Schroedl; Manoj Kumar 007; Kiana Hajebi; Morteza Ziyadi; Sriram Venkatapathy; Anil Ramakrishna; Rahul Gupta 001; Pradeep Natarajan (EMNLP (Industry Track), 2022)

Federated Learning with Noisy User Feedback. - Rahul Sharma; Anil Ramakrishna; Ansel MacLaughlin; Anna Rumshisky; Jimit Majmudar; Clement Chung; Salman Avestimehr; Rahul Gupta 001 (NAACL-HLT, 2022)

Joint Multi-Dimensional Model for Global and Time-Series Annotations. - Anil Ramakrishna; Rahul Gupta 001; Shrikanth Narayanan (IEEE Trans. Affect. Comput., 2022)

INVITE: a Testbed of Automatically Generated Invalid Questions to Evaluate Large Language Models for Hallucinations. - Anil Ramakrishna; Rahul Gupta 001; Jens Lehmann 001; Morteza Ziyadi (EMNLP (Findings), 2023)

Self-Healing Through Error Detection, Attribution, and Retraining. - Ansel MacLaughlin; Anna Rumshisky; Rinat Khaziev; Anil Ramakrishna; Yuval Merhav; Rahul Gupta 001 (ICASSP, 2023)

Sampling bias in NLU models: Impact and Mitigation. - Zefei Li; Anil Ramakrishna; Anna Rumshisky; Andy Rosenbaum; Saleh Soltan; Rahul Gupta 001 (INTERSPEECH, 2023)

FedMultimodal: A Benchmark for Multimodal Federated Learning. - Tiantian Feng; Digbalay Bose; Tuo Zhang; Rajat Hebbar; Anil Ramakrishna; Rahul Gupta 001; Mi Zhang 002; Salman Avestimehr; Shrikanth Narayanan (KDD, 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)

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)

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

Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (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)

Partial Federated Learning. - Tiantian Feng; Anil Ramakrishna; Jimit Majmudar; Charith Peris; Jixuan Wang; Clement Chung; Richard S. Zemel; Morteza Ziyadi; Rahul Gupta 001 (CoRR, 2024)

REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (CoRR, 2024)

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. - Duygu Nur Yaldiz; Yavuz Faruk Bakman; Baturalp Buyukates; Chenyang Tao; Anil Ramakrishna; Dimitrios Dimitriadis; Salman Avestimehr (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)

HARMONY: Hidden Activation Representations and Model Output-Aware Uncertainty Estimation for Vision-Language Models. - Erum Mushtaq; Zalan Fabian; Yavuz Faruk Bakman; Anil Ramakrishna; Mahdi Soltanolkotabi; Salman Avestimehr (CVPR Workshops, 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)

Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate. - Xiaomeng Jin; Zhiqi Bu; Bhanukiran Vinzamuri; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Mingyi Hong 001 (NAACL (Long Papers), 2025)

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. - Duygu Nur Yaldiz; Yavuz Faruk Bakman; Baturalp Buyukates; Chenyang Tao; Anil Ramakrishna; Dimitrios Dimitriadis; Jieyu Zhao; Salman Avestimehr (NAACL (Findings), 2025)

REAL Sampling: Boosting Factuality and Diversity of Open-ended Generation by Extrapolating the Entropy of an Infinitely Large LM. - Haw-Shiuan Chang; Nanyun Peng 001; Mohit Bansal; Anil Ramakrishna; Tagyoung Chung (Trans. Assoc. Comput. Linguistics, 2025)

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond. - Chongyu Fan; Jinghan Jia; Yihua Zhang; Anil Ramakrishna; Mingyi Hong 001; Sijia Liu 001 (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)

LUME: LLM Unlearning with Multitask Evaluations. - Anil Ramakrishna; Yixin Wan; Xiaomeng Jin; Kai-Wei Chang; Zhiqi Bu; Bhanukiran Vinzamuri; Volkan Cevher; Mingyi Hong 001; Rahul Gupta 001 (CoRR, 2025)

SemEval-2025 Task 4: Unlearning sensitive content from Large Language Models. - Anil Ramakrishna; Yixin Wan; Xiaomeng Jin; Kai-Wei Chang; Zhiqi Bu; Bhanukiran Vinzamuri; Volkan Cevher; Mingyi Hong 001; Rahul Gupta 001 (CoRR, 2025)

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning. - Yixin Wan; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Rahul Gupta 001 (CoRR, 2025)

Constrained Entropic Unlearning: A Primal-Dual Framework for Large Language Models. - Taha Entesari; Arman Hatami; Rinat Khaziev; Anil Ramakrishna; Mahyar Fazlyab (CoRR, 2025)

BLUR: A Bi-Level Optimization Approach for LLM Unlearning. - Hadi Reisizadeh; Jinghan Jia; Zhiqi Bu; Bhanukiran Vinzamuri; Anil Ramakrishna; Kai-Wei Chang; Volkan Cevher; Sijia Liu 001; Mingyi Hong 001 (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)