A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (HIS, 2002)

Missing values prediction with K2. - Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (Intell. Data Anal., 2002)

Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values. - Eduardo R. Hruschka; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (Australian Conference on Artificial Intelligence, 2003)

A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm. - Eduardo R. Hruschka; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (SBBD, 2003)

A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (Appl. Artif. Intell., 2003)

Feature Selection by Bayesian Networks. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (Canadian AI, 2004)

Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach. - Eduardo R. Hruschka; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (Australian Conference on Artificial Intelligence, 2004)

Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. - Eduardo R. Hruschka; Thiago F. Covoes; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (HIS, 2005)

Initializing an Exemplar Based Learning Process from a RuleNet Network. - Maria do Carmo Nicoletti; Lucas Baggio Figueira; Estevam R. Hruschka Jr. (HIS, 2005)

Missing Values Imputation for a Clustering Genetic Algorithm. - Eduardo R. Hruschka; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (ICNC (3), 2005)

Applying Bayesian Networks for Meteorological Data Mining. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (SGAI Conf. (Applications), 2005)

Selecting feature subsets for inducing classifiers using a committee of heterogeneous methods. - Daniel Monegatto Santoro; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (SMC, 2005)

Two Variants of the Constructive Neural Network Tiling Algorithm. - João Roberto Bertini Jr.; Maria do Carmo Nicoletti; Estevam R. Hruschka Jr.; Arthur Ramer (HIS, 2006)

VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr. (HIS, 2006)

A Comparative Evaluation of Constructive Neural Networks Methods using PRM and BCP as TLU Training Algorithms. - João Roberto Bertini Jr.; Maria do Carmo Nicoletti; Estevam R. Hruschka Jr. (SMC, 2006)

Bayesian Feature Selection for Clustering Problems. - Eduardo R. Hruschka; Estevam R. Hruschka Jr.; Thiago F. Covoes; Nelson F. F. Ebecken (J. Inf. Knowl. Manag., 2006)

Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (IEEE Congress on Evolutionary Computation, 2007)

A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms. - Sebastian D. C. de O. Galvão; Estevam R. Hruschka Jr. (DaWaK, 2007)

Feature-weighted k-Nearest Neighbor Classifier. - Diego P. Vivencio; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Edimilson Batista dos Santos; Sebastian D. C. de O. Galvão (FOCI, 2007)

BayesFuzzy: Using a Bayesian Classifier to Induce a Fuzzy Rule Base. - Estevam R. Hruschka Jr.; Heloisa de Arruda Camargo; Marcos Evandro Cintra; Maria do Carmo Nicoletti (FUZZ-IEEE, 2007)

Markov-Blanket Based Strategy for Translating a Bayesian Classifier into a Reduced Set of Classification Rules. - Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Vilma A. de Oliveira; Gláucia M. Bressan (HIS, 2007)

Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach. - Estevam R. Hruschka Jr.; Edimilson Batista dos Santos; Sebastian D. C. de O. Galvão (HIS, 2007)

Biomass Based Weed-Crop Competitiveness Classification Using Bayesian Networks. - Gláucia M. Bressan; Vilma A. de Oliveira; Estevam R. Hruschka Jr.; Maria C. Nicoletti (ISDA, 2007)

Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers A Comparative Approach. - Marcos Evandro Cintra; Heloisa de Arruda Camargo; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (ISDA, 2007)

WNB: A Weighted Naïve Bayesian Classifier. - Saul D. de S. S. Pedro; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (ISDA, 2007)

C-Focus-3: a C-Focus with a New Heuristic Search Strategy. - Daniel Monegatto Santoro; Maria do Carmo Nicoletti; Estevam R. Hruschka Jr. (ISDA, 2007)

Towards efficient variables ordering for Bayesian networks classifier. - Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (Data Knowl. Eng., 2007)

Fast Conditional Independence-based Bayesian Classifier. - Estevam R. Hruschka Jr.; Sebastian D. C. de O. Galvão (J. Comput. Sci. Eng., 2007)

Bayesian networks for imputation in classification problems. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (J. Intell. Inf. Syst., 2007)

Transferring neural network based knowledge into an exemplar-based learner. - Maria do Carmo Nicoletti; Lucas Baggio Figueira; Estevam R. Hruschka Jr. (Neural Comput. Appl., 2007)

BayesRule: A Markov-Blanket based procedure for extracting a set of probabilistic rules from Bayesian classifiers. - Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Vilma A. de Oliveira; Gláucia M. Bressan (Int. J. Hybrid Intell. Syst., 2008)

Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches. - Marcos Evandro Cintra; Heloisa de Arruda Camargo; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (J. Univers. Comput. Sci., 2008)

Toward Never Ending Language Learning. - Justin Betteridge; Andrew Carlson; Sue Ann Hong; Estevam R. Hruschka Jr.; Edith L. M. Law; Tom M. Mitchell; Sophie H. Wang (AAAI Spring Symposium: Learning by Reading and Learning to Read, 2009)

The Impact of Pruning BayesFuzzy Rule Set. - I-Hsien Yin; Estevam R. Hruschka Jr.; Heloisa de Arruda Camargo (ISDA, 2009)

Populating the Semantic Web by Macro-reading Internet Text. - Tom M. Mitchell; Justin Betteridge; Andrew Carlson; Estevam R. Hruschka Jr.; Richard C. Wang (ISWC, 2009)

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop. - Gláucia M. Bressan; Vilma A. de Oliveira; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (Eng. Appl. Artif. Intell., 2009)

On the influence of imputation in classification: practical issues. - Eduardo R. Hruschka; Antonio J. T. Garcia; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (J. Exp. Theor. Artif. Intell., 2009)

Toward an Architecture for Never-Ending Language Learning. - Andrew Carlson; Justin Betteridge; Bryan Kisiel; Burr Settles; Estevam R. Hruschka Jr.; Tom M. Mitchell (AAAI, 2010)

Gene ontology classification: Building high-level knowledge using genetic algorithms. - Laurence Rodrigues do Amaral; Estevam R. Hruschka Jr. (IEEE Congress on Evolutionary Computation, 2010)

A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (IEEE Congress on Evolutionary Computation, 2010)

Evolutionary Algorithm Using Random Multi-point Crossover Operator for Learning Bayesian Network Structures. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Nelson F. F. Ebecken (ICMLA, 2010)

Intelligent Classification System Using a Pruned Bayes Fuzzy Rule Set. - I-Hsien Yin; Estevam R. Hruschka Jr.; Heloisa de Arruda Camargo (ICMLA, 2010)

Centaurs - A Component-based Framework to Mine Large Graphs. - Ana Paula Appel; Estevam R. Hruschka Jr. (SBBD (Posters), 2010)

Coupled semi-supervised learning for information extraction. - Andrew Carlson; Justin Betteridge; Richard C. Wang; Estevam R. Hruschka Jr.; Tom M. Mitchell (WSDM, 2010)

Transgenic, an operator for evolutionary algorithms. - Laurence Rodrigues do Amaral; Estevam R. Hruschka Jr. (IEEE Congress on Evolutionary Computation, 2011)

Discovering Relations between Noun Categories. - Thahir Mohamed; Estevam R. Hruschka Jr.; Tom M. Mitchell (EMNLP, 2011)

Prophet - A Link-Predictor to Learn New Rules on NELL. - Ana Paula Appel; Estevam Rafael Hruschka Junior (ICDM Workshops, 2011)

Learning Bayesian Network structures using Multiple Offspring Sampling. - Edimilson Batista dos Santos; Nelson F. F. Ebecken; Estevam R. Hruschka Jr. (ISDA, 2011)

Minimização do Impacto do Problema de Desvio de Conceito por Meio de Acoplamento em Ambiente de Aprendizado Sem Fim (Minimizing the Impact of the Concept Drift Problem by Using a Framework of Endless Learning) [in Portuguese]. - Maísa Cristina Duarte; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti (STIL, 2011)

Bayesian network classifiers: Beyond classification accuracy. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (Intell. Data Anal., 2011)

A Bayesian imputation method for a clustering genetic algorithm. - Estevam R. Hruschka Jr.; Eduardo R. Hruschka; Nelson F. F. Ebecken (J. Comput. Methods Sci. Eng., 2011)

Never-ending learning principles in gene ontology classification using genetic algorithms. - Laurence Rodrigues do Amaral; Estevam Rafael Hruschka Junior (IEEE Congress on Evolutionary Computation, 2012)

Contradiction Detection and Ontology Extension in a Never-Ending Learning System. - Vinicius Oliverio; Estevam R. Hruschka Jr. (IBERAMIA, 2012)

Conversing Learning: Active Learning and Active Social Interaction for Human Supervision in Never-Ending Learning Systems. - Saulo D. de S. Pedro; Estevam R. Hruschka Jr. (IBERAMIA, 2012)

Representation and automatic learning of temporal relations between time periods with uncertain boundaries. - Maria C. Nicoletti; Flávia O. Santos de Sá Lisboa; Estevam R. Hruschka Jr.; Osvaldo Luiz De Oliveira (ISDA, 2012)

Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction. - Saurabh Verma; Estevam R. Hruschka Jr. (ECML/PKDD (2), 2012)

Collective intelligence as a source for machine learning self-supervision. - Saulo D. de S. Pedro; Estevam R. Hruschka Jr. (WI&C, 2012)

GraphDB - Storing Large Graphs on Secondary Memory. - Lucas Fonseca Navarro; Ana Paula Appel; Estevam Rafael Hruschka Junior (ADBIS (2), 2013)

Approach to Cold-Start Problem in Recommender Systems in the Context of Web-Based Education. - Reginaldo Aparecido Gotardo; Estevam Rafael Hruschka Junior; Sérgio Donizetti Zorzo (ICMLA (2), 2013)

Autonomously reviewing and validating the knowledge base of a never-ending learning system. - Saulo D. de S. Pedro; Ana Paula Appel; Estevam R. Hruschka Jr. (WWW (Companion Volume), 2013)

The construction of causal networks to estimate coral bleaching intensity. - Lilian Anne Krug; Douglas Francisco Marcolino Gherardi; José Stech; Zelinda Margarida Andrade Nery Leão; Ruy Kenji Papa Kikuchi; Estevam Rafael Hruschka Junior; David John Suggett (Environ. Model. Softw., 2013)

Coupling as Strategy for Reducing Concept-Drift in Never-ending Learning Environments. - Estevam R. Hruschka Jr.; Maisa C. Duarte; Maria C. Nicoletti (Fundam. Informaticae, 2013)

Automatic Learning of Temporal Relations Under the Closed World Assumption. - Maria C. Nicoletti; Flávia O. Santos de Sá Lisboa; Estevam R. Hruschka Jr. (Fundam. Informaticae, 2013)

Combining Classification and Clustering for Tweet Sentiment Analysis. - Luiz Fernando Sommaggio Coletta; Nádia Félix F. da Silva; Eduardo R. Hruschka; Estevam R. Hruschka Jr. (BRACIS, 2014)

Never-ending ontology extension through machine reading. - Paulo Henrique Barchi; Estevam Rafael Hruschka Junior (HIS, 2014)

Exploring two views of coreference resolution in a never-ending learning system. - Maisa C. Duarte; Estevam R. Hruschka Jr. (HIS, 2014)

Analyzing the use of obvious and generalized association rules in a large knowledge base. - Rafael Garcia Leonel Miani; Estevam Rafael Hruschka Junior (HIS, 2014)

How to read the web in portuguese using the never-ending language learner's principles. - Maisa C. Duarte; Estevam R. Hruschka Jr. (ISDA, 2014)

Biocom_Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble. - Nádia Félix F. da Silva; Estevam R. Hruschka Jr.; Eduardo R. Hruschka (SemEval@COLING, 2014)

Tweet sentiment analysis with classifier ensembles. - Nádia Félix F. da Silva; Eduardo R. Hruschka; Estevam R. Hruschka Jr. (Decis. Support Syst., 2014)

The influences of canonical evolutionary algorithm operators and variable orderings in learning Bayesian classifiers from data. - Edimilson Batista dos Santos; Estevam R. Hruschka Jr.; Maria do Carmo Nicoletti; Nelson F. F. Ebecken (Int. J. Hybrid Intell. Syst., 2014)

Transgenic: An evolutionary algorithm operator. - Laurence Rodrigues do Amaral; Estevam R. Hruschka Jr. (Neurocomputing, 2014)

Never-Ending Learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha Pratim Talukdar; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matthew Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; Kathryn Mazaitis; et al. (AAAI, 2015)

Editorial. - Dunja Mladenic; Estevam R. Hruschka Jr.; Marko Grobelnik (J. Web Semant., 2015)

Finding Inference Rules Using Graph Mining in Ontological Knowledge Bases. - Lucas Fonseca Navarro; Estevam R. Hruschka Jr.; Ana Paula Appel (BRACIS, 2016)

Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System. - Edimilson Batista dos Santos; Massilon Lourenço Fernandes; Estevam R. Hruschka Jr.; Maísa Cristina Duarte (ISDA, 2016)

Cognitive Conversation Language - CCL. - Wesley Willy Oliveira de Souza; Estevam Rafael Hruschka Junior (ISDA, 2016)

Lifelong Machine Learning and Computer Reading the Web. - Zhiyuan Chen 001; Estevam R. Hruschka Jr.; Bing Liu 001 (KDD, 2016)

Ontological Networks: Mapping Ontological Knowledge Bases into Graphs. - Lucas Fonseca Navarro; Estevam Rafael Hruschka Junior; Ana Paula Appel (WWW (Companion Volume), 2016)

Reports of the 2016 AAAI Workshop Program. - Stefano V. Albrecht; Bruno Bouchard 001; John S. Brownstein; David L. Buckeridge; Cornelia Caragea; Kevin M. Carter 001; Adnan Darwiche; Blaz Fortuna; Yannick Francillette; Sébastien Gaboury; C. Lee Giles; Marko Grobelnik; et al. (AI Mag., 2016)

Using unsupervised information to improve semi-supervised tweet sentiment classification. - Nádia Félix Felipe da Silva; Luiz F. S. Coletta; Eduardo R. Hruschka; Estevam R. Hruschka Jr. (Inf. Sci., 2016)

Correcting Inconsistencies through Association Rules in Temporal Large Growing Knowledge Bases. - Rafael Garcia Leonel Miani; Estevam Rafael Hruschka Junior (BRACIS, 2017)

Specific temporal association rules and temporal correlations to enlarge and detect inconsistencies in a large growing knowledge base. - Rafael Garcia; Leonel Miani; Estevam Rafael Hruschka Junior (ICNC-FSKD, 2017)

Merging knowledge bases in different languages. - Jerónimo Hernández-González; Estevam R. Hruschka Jr.; Tom M. Mitchell (TextGraphs@ACL, 2017)

Eliminating Redundant and Irrelevant Association Rules in Large Knowledge Bases. - Rafael Garcia Leonel Miani; Estevam Rafael Hruschka Junior (ICEIS (1), 2018)

NELL2RDF: Reading the Web, Tracking the Provenance, and Publishing it as Linked Data. - José M. Giménez-García; Maísa Cristina Duarte; Antoine Zimmermann; Christophe Gravier; Estevam R. Hruschka Jr.; Pierre Maret (CKGSemStats@ISWC, 2018)

Never-ending learning. - Tom M. Mitchell; William W. Cohen; Estevam R. Hruschka Jr.; Partha P. Talukdar; Bo Yang 011; Justin Betteridge; Andrew Carlson; Bhavana Dalvi Mishra; Matt Gardner 001; Bryan Kisiel; Jayant Krishnamurthy; Ni Lao; et al. (Commun. ACM, 2018)

NELL2RDF: Reading the Web, and Publishing it as Linked Data. - José M. Giménez-García; Maisa C. Duarte; Antoine Zimmermann; Christophe Gravier; Estevam R. Hruschka Jr.; Pierre Maret (CoRR, 2018)

Coupling for Coreference Resolution in a Never-ending Learning System. - Felipe Quécole; Maísa Cristina Duarte; Estevam Rafael Hruschka Junior (J. Inf. Data Manag., 2018)

Bayesian Networks for Inference and Discovery of Semantic Relations in a Never-Ending Learning System. - Edimilson Batista dos Santos; Igor Henrique P. Rodrigues; Estevam R. Hruschka Jr.; Lucas Rezende Bruno (BRACIS, 2019)

Crowd-Powered Systems to Diminish the Effects of Semantic Drift. - Saulo D. de S. Pedro; Estevam R. Hruschka Jr. (HAIS, 2019)

Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward. - Daniel Severo 001; Flávio Amaro; Estevam R. Hruschka Jr.; André Soares de Moura Costa (CoRR, 2019)

Data-Driven Never-Ending Learning Question Answering Systems. - Estevam R. Hruschka Jr. (KDD, 2020)

Applying Never-Ending Learning (NEL) Principles to Build a Gene Ontology (GO) Biocurator. - Laurence Rodrigues do Amaral; Alexandre Henrick da Silva Alves; Raphael de Lima Mendes; Matheus de Souza Gomes; Pedro Luiz Lima Bertarini; Estevam Rafael Hruschka (CEC, 2021)

WIT: Workshop on deriving Insights from user-generated Text. - Estevam Hruschka; Tom M. Mitchell; Marko Grobelnik; Behzad Golshan (KDD, 2021)

TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration. - Dongjin Choi; Sara Evensen; Çagatay Demiralp; Estevam Hruschka (WWW (Companion Volume), 2021)

Low-resource Interactive Active Labeling for Fine-tuning Language Models. - Seiji Maekawa; Dan Zhang 025; Hannah Kim 001; Sajjadur Rahman; Estevam Hruschka (EMNLP (Findings), 2022)

Low-resource Entity Set Expansion: A Comprehensive Study on User-generated Text. - Yutong Shao; Nikita Bhutani; Sajjadur Rahman; Estevam Hruschka (NAACL-HLT (Findings), 2022)

Zero-shot Triplet Extraction by Template Infilling. - Bosung Kim; Hayate Iso; Nikita Bhutani; Estevam Hruschka; Ndapa Nakashole (CoRR, 2022)

Zero-shot Triplet Extraction by Template Infilling. - Bosung Kim; Hayate Iso; Nikita Bhutani; Estevam Hruschka; Ndapa Nakashole; Tom M. Mitchell (IJCNLP (1), 2023)

Tutorials at The Web Conference 2023. - Valeria Fionda; Olaf Hartig; Reyhaneh Abdolazimi; Sihem Amer-Yahia; Hongzhi Chen; Xiao Chen 016; Peng Cui 001; Jeffrey Dalton 001; Xin Luna Dong; Lisette Espín-Noboa; Wenqi Fan; Manuela Fritz; et al. (WWW (Companion Volume), 2023)

Weedle: Composable Dashboard for Data-Centric NLP in Computational Notebooks. - Nahyun Kwon; Hannah Kim 001; Sajjadur Rahman; Dan Zhang 025; Estevam Hruschka (WWW (Companion Volume), 2023)

MEGAnno: Exploratory Labeling for NLP in Computational Notebooks. - Dan Zhang 025; Hannah Kim 001; Rafael Li Chen; Eser Kandogan; Estevam Hruschka (CoRR, 2023)

Towards Multifaceted Human-Centered AI. - Sajjadur Rahman; Hannah Kim 001; Dan Zhang 025; Estevam Hruschka; Eser Kandogan (CoRR, 2023)

Rethinking Language Models as Symbolic Knowledge Graphs. - Vishwas Mruthyunjaya; Pouya Pezeshkpour; Estevam Hruschka; Nikita Bhutani (CoRR, 2023)

Distilling Large Language Models using Skill-Occupation Graph Context for HR-Related Tasks. - Pouya Pezeshkpour; Hayate Iso; Thom Lake; Nikita Bhutani; Estevam Hruschka (CoRR, 2023)

Knowledge Graphs are not Created Equal: Exploring the Properties and Structure of Real KGs. - Nedelina Teneva; Estevam Hruschka (CoRR, 2023)

Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks. - Aditi Mishra; Sajjadur Rahman; Kushan Mitra; Hannah Kim 001; Estevam Hruschka (ACL (Findings), 2024)

Less is More for Long Document Summary Evaluation by LLMs. - Yunshu Wu; Hayate Iso; Pouya Pezeshkpour; Nikita Bhutani; Estevam Hruschka (EACL (2), 2024)

Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions. - Pouya Pezeshkpour; Estevam Hruschka (NAACL-HLT (Findings), 2024)

Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions. - Pouya Pezeshkpour; Eser Kandogan; Nikita Bhutani; Sajjadur Rahman; Tom M. Mitchell; Estevam Hruschka (CoRR, 2024)

Knowledge Acquisition and Integration with Expert-in-the-loop. - Sajjadur Rahman; Frederick Choi; Hannah Kim 001; Dan Zhang 025; Estevam Hruschka (CoRR, 2024)

A Blueprint Architecture of Compound AI Systems for Enterprise. - Eser Kandogan; Sajjadur Rahman; Nikita Bhutani; Dan Zhang 025; Rafael Li Chen; Kushan Mitra; Sairam Gurajada; Pouya Pezeshkpour; Hayate Iso; Yanlin Feng; Hannah Kim 001; Chen Shen 009; et al. (CoRR, 2024)

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization. - Catarina G. Belém; Pouya Pezeskhpour; Hayate Iso; Seiji Maekawa; Nikita Bhutani; Estevam Hruschka (CoRR, 2024)

Retrieval Augmented Generation in the Wild: A System 2 Perspective. - Sajjadur Rahman; Dan Zhang 025; Nikita Bhutani; Estevam Hruschka; Eser Kandogan (IEEE Data Eng. Bull., 2024)

FactLens: Benchmarking Fine-Grained Fact Verification. - Kushan Mitra; Dan Zhang 025; Sajjadur Rahman; Estevam Hruschka (ACL (Findings), 2025)

Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI. - Eser Kandogan; Nikita Bhutani; Dan Zhang 025; Rafael Li Chen; Sairam Gurajada; Estevam Hruschka (ICDEW, 2025)

From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization. - Catarina G. Belém; Pouya Pezeshkpour; Hayate Iso; Seiji Maekawa; Nikita Bhutani; Estevam Hruschka (NAACL (Findings), 2025)

Evaluating Bias in LLMs for Job-Resume Matching: Gender, Race, and Education. - Hayate Iso; Pouya Pezeshkpour; Nikita Bhutani; Estevam Hruschka (NAACL (Industry Track), 2025)

Natural Language Processing for Human Resources: A Survey. - Naoki Otani; Nikita Bhutani; Estevam Hruschka (NAACL (Industry Track), 2025)

Multi-Conditional Ranking with Large Language Models. - Pouya Pezeshkpour; Estevam Hruschka (NAACL (Long Papers), 2025)

Learning Beyond the Surface: How Far Can Continual Pre-Training with LoRA Enhance LLMs' Domain-Specific Insight Learning? - Pouya Pezeshkpour; Estevam Hruschka (CoRR, 2025)

Insight-RAG: Enhancing LLMs with Insight-Driven Augmentation. - Pouya Pezeshkpour; Estevam Hruschka (CoRR, 2025)

Mixed Signals: Decoding VLMs' Reasoning and Underlying Bias in Vision-Language Conflict. - Pouya Pezeshkpour; Moin Aminnaseri; Estevam Hruschka (CoRR, 2025)

Towards Probabilistic Question Answering Over Tabular Data. - Chen Shen 009; Sajjadur Rahman; Estevam Hruschka (CoRR, 2025)

RECAP: REwriting Conversations for Intent Understanding in Agentic Planning. - Kushan Mitra; Dan Zhang 025; Hannah Kim 001; Estevam Hruschka (CoRR, 2025)

AIPOM: Agent-aware Interactive Planning for Multi-Agent Systems. - Hannah Kim 001; Kushan Mitra; Chen Shen 009; Dan Zhang 025; Estevam Hruschka (CoRR, 2025)

Towards Reliable Benchmarking: A Contamination Free, Controllable Evaluation Framework for Multi-step LLM Function Calling. - Seiji Maekawa; Jackson Hassell; Pouya Pezeshkpour; Tom M. Mitchell; Estevam Hruschka (CoRR, 2025)

Verification-Aware Planning for Multi-Agent Systems. - Tianyang Xu; Dan Zhang 025; Kushan Mitra; Estevam Hruschka (CoRR, 2025)

Learning from Supervision with Semantic and Episodic Memory: A Reflective Approach to Agent Adaptation. - Jackson Hassell; Dan Zhang 025; Hannah Kim 001; Tom M. Mitchell; Estevam Hruschka (CoRR, 2025)