Hugging Face
The PortNLP lab is led by Dr. Ameeta Agrawal.
At PortNLP, we explore new ways to advance language technologies -- from understanding complex texts to generating multilingual summaries. We aim to design systems that are effective, efficient, fair, and human-centered. We envision a future where language technologies are trustworthy and useful in everyday life.
PortNLP started in 2021 with PI and two students focusing on a few specific domains of text summarization and multilingual language models. As we have continued to grow, our past students and present members are contributing to a wide range of topics in natural language understanding and processing.
We are also affiliated with the Coco Lab, a sister research group focused on the intersection of computer science, management, and anthropology.
Research Themes
Language Understanding
- Long Context
- Ambiguity
- Contextual Grounding
Language Generation
- Summarization
- Multilingual Modeling
- Efficient NLP
Human-Centered NLP
- Affective Modeling
- Conversational Systems
- Bias Mitigation
Recent News
April 2026
3 Papers Accepted at ACL 2026!
- No-Worse Context-Aware Decoding: Preventing Neutral Regression in Context-Conditioned Generation, Yufei Tao, Ameeta Agrawal
- ThreadSumm: Summarization of Nested Discourse Threads Using Tree of Thoughts, Olubusayo Olabisi, Ekata Mitra, Ameeta Agrawal
- Self-Explaining Hate Speech Detection with Moral Rationales, Francielle Vargas, Jackson Trager, Diego Alves, Surendrabikram Thapa, Matteo Guida, Berk Atil, Daryna Dementieva, Andrew Smart, Ameeta Agrawal
March 2026
- Neurosymbolic Artificial Intelligence [Journal]: Robust Long-Context Multilingual Retrieval and Reasoning Enabled by Combined Neural and Symbolic Techniques, Sina Bagheri Nezhad, Ameeta Agrawal.
- AI, Computer Science and Robotics Technology [Journal]: Engagingness in Open-Domain Dialogue Systems: A Systematic Survey of Datasets, Metrics, and Methods, Ekata Mitra, Amila Ferron, Ameeta Agrawal
January 2026
- Accepted at the Findings of EACL 2026: SymCode: A Neurosymbolic Approach to Mathematical Reasoning via Verifiable Code Generation, Sina Bagheri Nezhad, Yao Li, Ameeta Agrawal
- Accetped at AIMedHealth (AAAI 2026): From Policy to Logic for Efficient and Interpretable Coverage Assessment, Rhitabrat Pokharel, Hamid Reza Hassanzadeh, Ameeta Agrawal
Sponsors
This lab is grateful for the funding support from the following grants and awards:
