collaborators

8 papers

cs.CL2026

EnSI-RAG: Entity-Structure-Indexed Retrieval-Augmented Generation for Long-Document Question Answering

Xuanyu Meng, Jiashuo Sun, Jash Rajesh Parekh +1

Question answering (QA) over long, connected documents remains challenging because relevant evidence may span multiple entities and their relationships. Existing retrieval-augmente…

cs.HC2026

AI-Mediated Negotiation: Design Reflections and Lessons

Veda Duddu, Jash Rajesh Parekh, Andy Mao +4

Conversational AI promises a new kind of preparation for high-stakes workplace negotiations -- personalized, interactive, and capable of simulating realistic resistance. That promi…

cs.CL2026

Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering

Jash Rajesh Parekh, Wonbin Kweon, Joey Chan +7

Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is inherently conditional: nearly every…

cs.AI2026

Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation

Jiashuo Sun, Jimeng Shi, Yixuan Xie +10

Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on multi-hop questions, where so…

cs.HC2026

Not My Truce: Personality Differences in AI-Mediated Workplace Negotiation

Veda Duddu, Jash Rajesh Parekh, Andy Mao +4

AI-driven conversational coaching is increasingly used to support workplace negotiation, yet prior work assumes uniform effectiveness across users. We challenge this assumption by…

cs.CL2026

Structure-Augmented Reasoning Generation

Jash Rajesh Parekh, Pengcheng Jiang, Jiawei Han

Recent advances in Large Language Models (LLMs) have significantly improved complex reasoning capabilities. Retrieval-Augmented Generation (RAG) has further extended these capabili…