5 papers
Adaptive Adversaries: A Multi-Turn, Multi-LLM Benchmark for LLM Agent Security
Devina Jain, David Hartmann, Chuan Li
LLM-based agents process external content, exposing them to prompt injection and multi-turn manipulation. Most safety benchmarks evaluate defenders against fixed attack pools colle…
ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents
Zhuofeng Li, Yi Lu, Dongfu Jiang +7
The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-based reviewers often generate s…
Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance
Weida Liang, Yiyou Sun, Shuyuan Nan +3
Example-based guidance is widely used to improve mathematical reasoning at inference time, yet its effectiveness is highly unstable across problems and models-even when the guidanc…
Inference-Time Rethinking with Latent Thought Vectors for Math Reasoning
Deqian Kong, Minglu Zhao, Aoyang Qin +10
Standard chain-of-thought reasoning generates a solution in a single forward pass, committing irrevocably to each token and lacking a mechanism to recover from early errors. We int…
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu +8
We propose a novel class of language models, Latent Thought Models (LTMs), which incorporate explicit latent thought vectors that follow an explicit prior model in latent space. Th…