7 citations · 7 across the 6 of their papers we have counts for
6 papers
EMBER: Efficient Memory via Budgeted Evidence Retention for Long-Horizon Agents
Yilong Li, Suman Banerjee, Tong Che
Long-horizon agents can archive large histories, but future answers still incur retrieval, rereading, and context costs. When retained memory misses answer-relevant evidence, the s…
Cast a Wider Net: Coordinated Pass@K Policy Optimization for Code Reasoning
Yilong Li, Suman Banerjee, Tong Che
Repeated sampling with a verifier is the standard way to allocate test-time compute for code generation, with pass@ as the canonical metric. Yet the standard policy class draws…
Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety
Can Jin, Rui Wu, Tong Che +10
Ensuring that Large Language Models (LLMs) adhere to safety principles without refusing benign requests remains a significant challenge. While OpenAI introduces deliberative alignm…
AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
Can Jin, Yang Zhou, Qixin Zhang +8
Test-time scaling strategies for Large Language Models predominantly rely on either reinforcement learning with sparse outcome rewards or search-based methods guided by static Proc…
From Hallucination to Reliability: Generative Modeling and the Structure of Scientific Inference
Charles Rathkopf
Generative AI is increasingly used in science, but is unavoidably prone to hallucination. I develop a reliabilist account of how generative AI nevertheless gives rise to new scient…
LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation
Can Jin, Ying Li, Mingyu Zhao +6
Visual prompting has gained popularity as a method for adapting pre-trained models to specific tasks, particularly in the realm of parameter-efficient tuning. However, existing vis…