5 citations · 5 across the 5 of their papers we have counts for
5 papers
SBCO: Self-Supervised, Verifier-Grounded Harness Optimization For Planning Agents
Vivek Kulkarni, Sudipta Paul, Aounon Kumar +2
Self-improving agents seek to reduce the human engineering effort behind AI systems by enabling them to evolve and self-improve their performance over time. Recently, methods like…
PROGRESS: Coverage-guided RL to Train Search-augmented LLM Agent
Sudipta Paul, Vijay Srinivasan, Vivek Kulkarni +4
Existing search-augmented LLM agents are trained using Reinforcement Learning to boost its reasoning capabilities. However, these approaches primarily rely on outcome-level rewards…
Detecting LLM-Generated Peer Reviews
Vishisht Rao, Aounon Kumar, Himabindu Lakkaraju +1
The integrity of peer review is fundamental to scientific progress, but the rise of large language models (LLMs) has introduced concerns that some reviewers may rely on these tools…
Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models
Martin Pawelczyk, Lillian Sun, Zhenting Qi +2
The rapid proliferation of generative AI, especially large language models, has led to their integration into a variety of applications. A key phenomenon known as weak-to-strong ge…
MedSafetyBench: Evaluating and Improving the Medical Safety of Large Language Models
Tessa Han, Aounon Kumar, Chirag Agarwal +1
As large language models (LLMs) develop increasingly sophisticated capabilities and find applications in medical settings, it becomes important to assess their medical safety due t…