7 papers
Mosaic: Runtime-Efficient Multi-Agent Embodied Planning
Kunjal Panchal, Saayan Mitra, Sunav Choudhary +3
LLM-based multi-agent embodied planning remains impractical due to prohibitively high execution latency. We identify failed actions as the dominant bottleneck, stemming from two co…
An Interactive Paradigm for Deep Research
Lin Ai, Victor S. Bursztyn, Xiang Chen +2
Recent advances in large language models (LLMs) have enabled deep research systems that synthesize comprehensive, report-style answers to open-ended queries by combining retrieval,…
TeamFusion: Supporting Open-ended Teamwork with Multi-Agent Systems
Jiale Liu, Victor S. Bursztyn, Lin Ai +4
In open-ended domains, teams must reconcile diverse viewpoints to produce strong deliverables. Answer aggregation approaches commonly used in closed domains are ill-suited to this…
SQLSpace: A Representation Space for Text-to-SQL to Discover and Mitigate Robustness Gaps
Neha Srikanth, Victor Bursztyn, Puneet Mathur +1
We introduce SQLSpace, a human-interpretable, generalizable, compact representation for text-to-SQL examples derived with minimal human intervention. We demonstrate the utility of…
Disambiguation in Conversational Question Answering in the Era of LLMs and Agents: A Survey
Md Mehrab Tanjim, Yeonjun In, Xiang Chen +8
Ambiguity remains a fundamental challenge in Natural Language Processing (NLP) due to the inherent complexity and flexibility of human language. With the advent of Large Language M…
FigCaps-HF: A Figure-to-Caption Generative Framework and Benchmark with Human Feedback
Ashish Singh, Ashutosh Singh, Prateek Agarwal +10
Captions are crucial for understanding scientific visualizations and documents. Existing captioning methods for scientific figures rely on figure-caption pairs extracted from docum…