23 citations · 124 across the 30 of their papers we have counts for
9 papers · 1 filter
POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events
Sai Vallurupalli, Sayontan Ghosh, Katrin Erk +2
Knowledge about outcomes is critical for complex event understanding but is hard to acquire. We show that by pre-identifying a participant in a complex event, crowd workers are abl…
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot +1
Prompting-based large language models (LLMs) are surprisingly powerful at generating natural language reasoning steps or Chains-of-Thoughts (CoT) for multi-step question answering…
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples
Mohaddeseh Bastan, Mihai Surdeanu, Niranjan Balasubramanian
Natural language inference (NLI) is critical for complex decision-making in biomedical domain. One key question, for example, is whether a given biomedical mechanism is supported b…
Text-Derived Knowledge Helps Vision: A Simple Cross-modal Distillation for Video-based Action Anticipation
Sayontan Ghosh, Tanvi Aggarwal, Minh Hoai +1
Anticipating future actions in a video is useful for many autonomous and assistive technologies. Most prior action anticipation work treat this as a vision modality problem, where…
Efficient Methods for Natural Language Processing: A Survey
Marcos Treviso, Ji-Ung Lee, Tianchu Ji +19
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance mea…
PASTA: A Dataset for Modeling Participant States in Narratives
Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen +3
The events in a narrative are understood as a coherent whole via the underlying states of their participants. Often, these participant states are not explicitly mentioned, instead…
Human Language Modeling
Nikita Soni, Matthew Matero, Niranjan Balasubramanian +1
Natural language is generated by people, yet traditional language modeling views words or documents as if generated independently. Here, we propose human language modeling (HuLM),…
SuMe: A Dataset Towards Summarizing Biomedical Mechanisms
Mohaddeseh Bastan, Nishant Shankar, Mihai Surdeanu +1
Can language models read biomedical texts and explain the biomedical mechanisms discussed? In this work we introduce a biomedical mechanism summarization task. Biomedical studies o…
Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot +1
Question-answering datasets require a broad set of reasoning skills. We show how to use question decompositions to teach language models these broad reasoning skills in a robust fa…