5 citations · 6 across the 10 of their papers we have counts for
5 papers · 1 filter
SMaRT: Select, Mix, and ReinvenT -- A Strategy Fusion Framework for LLM-Driven Reasoning and Planning
Nikhil Verma, Manasa Bharadwaj, Wonjun Jang +4
Large Language Models (LLMs) have redefined complex task automation with exceptional generalization capabilities. Despite these advancements, state-of-the-art methods rely on singl…
GEMMAS: Graph-based Evaluation Metrics for Multi Agent Systems
Jisoo Lee, Raeyoung Chang, Dongwook Kwon +2
Multi-agent systems built on language models have shown strong performance on collaborative reasoning tasks. However, existing evaluations focus only on the correctness of the fina…
OmniReflect: Discovering Transferable Constitutions for LLM agents via Neuro-Symbolic Reflections
Manasa Bharadwaj, Nikhil Verma, Kevin Ferreira
Efforts to improve Large Language Model (LLM) agent performance on complex tasks have largely focused on fine-tuning and iterative self-correction. However, these approaches often…
Cross-Attention Speculative Decoding
Wei Zhong, Manasa Bharadwaj, Yixiao Wang +2
Speculative decoding (SD) is a widely adopted approach for accelerating inference in large language models (LLMs), particularly when the draft and target models are well aligned. H…
The Hidden Space of Safety: Understanding Preference-Tuned LLMs in Multilingual context
Nikhil Verma, Manasa Bharadwaj
Alignment tuning has enabled large language models to excel in reasoning, instruction-following, and minimizing harmful generations. However, despite their widespread deployment, t…