Mihalcea, Rada

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Poria, S., Hazarika, D., Majumder, N., Naik, G., Cambria, E., & Mihalcea, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Emotion and Mood RecognitionSentiment Analysis and Opinion Mining

Cited by 1,416

Towards multimodal sentiment analysis: harvesting opinions from the web

Morency, L.-P., Mihalcea, R., & Doshi, P. (2011) · Proceedings of the 13th international conference on multimodal interfaces

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 470

A review of deep learning techniques for speech processing

Mehrish, A., Majumder, N., Bharadwaj, R., Mihalcea, R., & Poria, S. (2023) · Information Fusion

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 389

Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)

Castro, S., Hazarika, D., Pérez-Rosas, V., Zimmermann, R., Mihalcea, R., & Poria, S. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Sentiment Analysis and Opinion MiningHate Speech and Cyberbullying Detection

Cited by 243

Experiments in open domain deception detection

Pérez-Rosas, V., & Mihalcea, R. (2015) · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

Deception detection and forensic psychologyAuthorship Attribution and Profiling

Cited by 97

Logical Fallacy Detection

Jin, Z., Lalwani, A., Vaidhya, T., Shen, X., Ding, Y., Lyu, Z., Sachan, M., Mihalcea, R., & Schölkopf, B. (2022) · Findings of the Association for Computational Linguistics: EMNLP 2022

Linguistics and Discourse AnalysisTopic Modeling

Cited by 52

Women’s Syntactic Resilience and Men’s Grammatical Luck: Gender-Bias in Part-of-Speech Tagging and Dependency Parsing

Garimella, A., Banea, C., Hovy, D., & Mihalcea, R. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Natural Language Processing TechniquesAuthorship Attribution and Profiling

Cited by 41

Comparative Effects of Glucose-Lowering Medications on Kidney Outcomes in Type 2 Diabetes: The GRADE Randomized Clinical Trial

Wexler, D. J., de Boer, I. H., Ghosh, A., Younes, N., Bebu, I., Inzucchi, S. E., McGill, J. B., Mudaliar, S., Schade, D., Steffes, M. W., et al. (2023) · JAMA Internal Medicine

Chronic Kidney Disease and DiabetesDiabetes Treatment and Management

Cited by 39

CIDER: Commonsense Inference for Dialogue Explanation and Reasoning

Ghosal, D., Hong, P., Shen, S., Majumder, N., Mihalcea, R., & Poria, S. (2021) · Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue

Speech and dialogue systemsLogic, Reasoning, and Knowledge

Cited by 19

Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions

Borah, A., & Mihalcea, R. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Ethics and Social Impacts of AITopic Modeling

Cited by 15

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents

Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024) · Advances in Neural Information Processing Systems 37

Evolutionary Game Theory and CooperationMulti-Agent Systems and Negotiation

Cited by 14

Cooperate or Collapse: Emergence of Sustainable Cooperation in a Society of LLM Agents

Piatti, G., Jin, Z., Kleiman-Weiner, M., Schölkopf, B., Sachan, M., & Mihalcea, R. (2024) · arXiv

Evolutionary Game Theory and CooperationMulti-Agent Systems and Negotiation

Cited by 14

Evaluating the reliability of large language models for clinical data extraction in bladder cancer prognosis

Sun, D., Hadjiiski, L., Bruno, G., Gormley, J., Chan, H.-P., Caoili, E. M., Cohan, R. H., Alva, A., Mihalcea, R., Zhou, C., et al. (2025) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 9

Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines

Azab, M., Dadian, S., Nastase, V., An, L., & Mihalcea, R. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Biomedical Text Mining and OntologiesNatural Language Processing Techniques

Cited by 5

Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone

Mihalcea, R., Ignat, O., Bai, L., Borah, A., Chiruzzo, L., Jin, Z., Kwizera, C., Nwatu, J., Poria, S., & Solorio, T. (2024) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 4

How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks

Bai, L., Huang, Z., Wang, X., Sun, J., Mihalcea, R., Brynjolfsson, E., Pentland, A., & Pei, J. (2026) · arXiv

Software Engineering ResearchArtificial Intelligence Applications

Cited by 3

HI-TOM: A Benchmark for Evaluating Higher-Order Theory of Mind Reasoning in Large Language Models

He, Y., Wu, Y., Jia, Y., Mihalcea, R., Chen, Y., & Deng, N. (2023) · arXiv

Child and Animal Learning DevelopmentTopic Modeling

Cited by 1

Mind the (Belief) Gap: Group Identity in the World of LLMs

Borah, A., Houalla, M., & Mihalcea, R. (2025) · arXiv

Ethics and Social Impacts of AIMisinformation and Its Impacts

Cited by 1

When Ethics and Payoffs Diverge: LLM Agents in Morally Charged Social Dilemmas

Backmann, S., Piedrahita, D. G., Zhang, T. J., Tewolde, E., Mihalcea, R., Schölkopf, B., & Jin, Z. (2025) · arXiv

Ethics and Social Impacts of AIEvolutionary Game Theory and Cooperation

Cited by 0