most citedSelf-Resource Allocation in Multi-Agent LLM Systems

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Write Once, Check Many: Reusable Ledgers for Post-Hoc Policy Compliance Auditing of Agent Trajectories

Ashwin Nagarajan, Gursimran Panesar, Alicia Yang +3

Auditing LLM agents against policies is critical to ensure safety but requires rereading long trajectories once per policy. Can we instead record each trajectory once and reuse tha…

cs.AI2026

SafePro: Evaluating the Safety of Professional-Level AI Agents

Kaiwen Zhou, Shreedhar Jangam, Ashwin Nagarajan +7

Large language model-based agents are rapidly evolving from simple conversational assistants into autonomous systems capable of performing complex, professional-level tasks in vari…

cs.SD2025

The Name-Free Gap: Policy-Aware Stylistic Control in Music Generation

Ashwin Nagarajan, Hao-Wen Dong

Text-to-music models capture broad attributes such as instrumentation or mood, but fine-grained stylistic control remains an open challenge. Existing stylization methods typically…

cs.CV2025

"PhyWorldBench": A Comprehensive Evaluation of Physical Realism in Text-to-Video Models

Jing Gu, Xian Liu, Yu Zeng +8

Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains…

cs.MA2025★ 3 cited

Self-Resource Allocation in Multi-Agent LLM Systems

Alfonso Amayuelas, Jingbo Yang, Saaket Agashe +4

With the development of LLMs as agents, there is a growing interest in connecting multiple agents into multi-agent systems to solve tasks concurrently, focusing on their role in ta…