1 citations · 4 across the 13 of their papers we have counts for
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Assessing Adversarial Robustness of Latent Reasoning Models
Shaolong Chen, Ang Li, Mingjie Li +1
Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings substantial memory and inference cos…
VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval
Lexiang Hu, Yanzhao Zhang, Mingxin Li +5
Visually rich documents encode relevance through language, layout, structured visual elements, and corpus context, yet retrieval is typically evaluated by one-shot query--page matc…
Diagnosing Visual Ignorance in Vision-Language Models
Runyu Zhou, Qi Zhang, Qixun Wang +1
Vision-language models (VLMs) achieve high accuracy on many visual question-answering benchmarks, yet it remains unclear whether this accuracy reflects reliable use of the visual d…
TrustLDM: Benchmarking Trustworthiness in Language Diffusion Models
Yichuan Mo, Yukun Jiang, Yanbo Shi +4
The rapid development of Language Diffusion Models (LDMs) challenges the dominant position of auto-regressive competitors in language processing. However, their flexible, any-order…
Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
Mingjie Li, Wai Man Si, Michael Backes +2
Despite the impressive performance of general-purpose large language models (LLMs), they often require fine-tuning or post-training to excel at specific tasks. For instance, large…