1 citations · 1 across the 3 of their papers we have counts for
5 papers · 1 filter
AccidentBench: Benchmarking Multimodal Understanding and Reasoning in Vehicle Accidents and Beyond
Shangding Gu, Xiaohan Wang, Donghao Ying +9
Rapid advances in multimodal models demand benchmarks that rigorously evaluate understanding and reasoning in safety-critical, dynamic real-world settings. We present AccidentBench…
StyleBench: Evaluating thinking styles in Large Language Models
Junyu Guo, Shangding Gu, Ming Jin +2
Structured reasoning can improve the inference performance of large language models (LLMs), but it also introduces computational cost and control constraints. When additional reaso…
Few-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond
Shangding Gu, Donghao Ying, Ming Jin +4
We introduce Model Feedback Learning (MFL), a novel test-time optimization framework for optimizing inputs to pre-trained AI models or deployed hardware systems without requiring a…
Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
Shangding Gu, Laixi Shi, Muning Wen +5
Driven by inherent uncertainty and the sim-to-real gap, robust reinforcement learning (RL) seeks to improve resilience against the complexity and variability in agent-environment s…
Don't Trade Off Safety: Diffusion Regularization for Constrained Offline RL
Junyu Guo, Zhi Zheng, Donghao Ying +4
Constrained reinforcement learning (RL) seeks high-performance policies under safety constraints. We focus on an offline setting where the agent has only a fixed dataset -- common…