19 citations · 34 across the 7 of their papers we have counts for
8 papers
Beyond Semantic Manipulation: Token-Space Attacks on Reward Models
Yuheng Zhang, Mingyue Huo, Minghao Zhu +2
Reward models (RMs) are widely used as optimization targets in reinforcement learning from human feedback (RLHF), yet they remain vulnerable to reward hacking. Existing attacks mai…
CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs
Sijia Chen, Xiaomin Li, Mengxue Zhang +3
Large language models (LLMs) are increasingly deployed in medical contexts, raising critical concerns about safety, alignment, and susceptibility to adversarial manipulation. While…
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions
Mengxue Zhang, Neil Heffernan, Andrew Lan
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for…
Interpretable Math Word Problem Solution Generation Via Step-by-step Planning
Mengxue Zhang, Zichao Wang, Zhichao Yang +2
Solutions to math word problems (MWPs) with step-by-step explanations are valuable, especially in education, to help students better comprehend problem-solving strategies. Most exi…
Algebra Error Classification with Large Language Models
Hunter McNichols, Mengxue Zhang, Andrew Lan
Automated feedback as students answer open-ended math questions has significant potential in improving learning outcomes at large scale. A key part of automated feedback systems is…
Automatic Short Math Answer Grading via In-context Meta-learning
Mengxue Zhang, Sami Baral, Neil Heffernan +1
Automatic short answer grading is an important research direction in the exploration of how to use artificial intelligence (AI)-based tools to improve education. Current state-of-t…
Math Operation Embeddings for Open-ended Solution Analysis and Feedback
Mengxue Zhang, Zichao Wang, Richard Baraniuk +1
Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students…
Evaluating the Performance of Reinforcement Learning Algorithms
Scott M. Jordan, Yash Chandak, Daniel Cohen +2
Performance evaluations are critical for quantifying algorithmic advances in reinforcement learning. Recent reproducibility analyses have shown that reported performance results ar…