16 citations · 16 across the 2 of their papers we have counts for
4 papers
What Is Missing: Interpretable Ratings for Large Language Model Outputs
Nicholas Stranges, Yimin Yang
Current Large Language Model (LLM) preference learning methods such as Proximal Policy Optimization and Direct Preference Optimization learn from direct rankings or numerical ratin…
SPL-LNS: Sampling-Enhanced Large Neighborhood Search for Solving Integer Linear Programs
Shengyu Feng, Zhiqing Sun, Yiming Yang
Large Neighborhood Search (LNS) is a common heuristic in combinatorial optimization that iteratively searches over a large neighborhood of the current solution for a better one. Re…
Improve Vision Language Model Chain-of-thought Reasoning
Ruohong Zhang, Bowen Zhang, Yanghao Li +6
Chain-of-thought (CoT) reasoning in vision language models (VLMs) is crucial for improving interpretability and trustworthiness. However, current training recipes lack robust CoT r…
DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems
Ruizhong Qiu, Zhiqing Sun, Yiming Yang
Recently, deep reinforcement learning (DRL) models have shown promising results in solving NP-hard Combinatorial Optimization (CO) problems. However, most DRL solvers can only scal…