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Sreyashi Nag

7 accepted papers

2025

EcomScriptBench: A Multi-task Benchmark for E-commerce Script Planning via Step-wise Intention-Driven Product Association

ACL 2025long

Goal-oriented script planning, or the ability to devise coherent sequences of actions toward specific goals, is commonly employed by humans to plan for typical activities. In e-commerce, customers increasingly seek LLM-based assistants to generate scripts and recommend products at each step, thereby…

Cited by 0SourcePDFScholar
2025

Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data

NAACL 2025findings

In real-world NLP applications, Large Language Models (LLMs) offer promising solutions due to their extensive training on vast datasets. However, the large size and high computation demands of LLMs limit their practicality in many applications, especially when further fine-tuning is required. To add…

2025

Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning

ACL 2025finding

Large language models (LLMs) have demonstrated remarkable success across a wide range of tasks; however, they still encounter challenges in reasoning tasks that require understanding and inferring relationships between distinct pieces of information within text sequences. This challenge is particula…

Cited by 0SourcePDFScholar
2025

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains

NAACL 2025long

Retrieval-augmented generation (RAG) enhances the question answering (QA) abilities of large language models (LLMs) by integrating external knowledge. However, adapting general-purpose RAG systems to specialized fields such as science and medicine poses unique challenges due to distribution shifts a…

Cited by 2SourcePDFScholar
2024

IterAlign: Iterative Constitutional Alignment of Large Language Models

NAACL 2024long

With the rapid development of large language models (LLMs), aligning LLMs with human values and societal norms to ensure their reliability and safety has become crucial. Reinforcement learning with human feedback (RLHF) and Constitutional AI (CAI) have been proposed for LLM alignment. However, these…

2024

Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark

EMNLP 2024main

The adoption of large language models (LLMs) to assist clinicians has attracted remarkable attention. Existing works mainly adopt the close-ended question-answering (QA) task with answer options for evaluation. However, many clinical decisions involve answering open-ended questions without pre-set o…

2023

Improving Consistency for Text Summarization with Energy Functions

EMNLP 2023short findings

Current abstractive summarization models often generate inconsistent content, i.e. texts that are not directly inferable from the source document, are not consistent with respect to world knowledge, or are self-contradictory. These inconsistencies motivate a new consistency taxonomy that we define a…

Cited by 0SourceScholar