12 papers
From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves
Haritz Puerto, Haonan Li, Xudong Han +2
Large reasoning models (LRMs) produce reasoning traces (RTs) that often contain sensitive information. These leaky thoughts are difficult to control and frequently violate explicit…
Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety
Xingjun Ma, Yifeng Gao, Yixu Wang +45
The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…
Training and Benchmarking Code Generation for Physics-Inspired Animations
Yanan Wang, Renxi Wang, Yongxin Wang +5
Large language models (LLMs) have been widely studied in areas such as mathematical reasoning, complex coding, and scientific problem solving. However, their ability to generate ex…
SCALAR: Scientific Citation-based Live Assessment of Long-context Academic Reasoning
Renxi Wang, Honglin Mu, Liqun Ma +5
Long-context understanding has emerged as a critical capability for large language models (LLMs). However, evaluating this ability remains challenging. We present SCALAR, a benchma…
Cross-Cultural Transfer of Commonsense Reasoning in LLMs: Evidence from the Arab World
Saeed Almheiri, Rania Hossam, Mena Attia +4
Large language models (LLMs) often reflect Western-centric biases, limiting their effectiveness in diverse cultural contexts. Although some work has explored cultural alignment, th…
AgentFly: Extensible and Scalable Reinforcement Learning for LM Agents
Renxi Wang, Rifo Ahmad Genadi, Bilal El Bouardi +5
Language model (LM) agents have gained significant attention for their ability to autonomously complete tasks through interactions with environments, tools, and APIs. LM agents are…