7 papers
Analog Cosmology in a Quenched Bose-Einstein Condensate Bubble
Ruotong Zhai, Brendan Rhyno, Zain Mehdi +3
Recent interest and realization of ultracold bosons confined in shell-shaped, or bubble, traps have opened up several directions in the study of Bose-Einstein condensates (BECs) in…
Recommender System as Slow and Fast Thinkers
Zichen Yuan, Xiaoxuan Dong, Linkun Dai +8
Sequential recommendation models are foundational to modern personalized services, yet their effectiveness varies substantially across heterogeneous user environments. In particula…
Risk-Aware Reranking for Agentic Tool Retrieval
Qinfei Li, Xiaoxuan Dong, Jin Zhang +6
Tool retrieval determines which external tools are exposed to an LLM agent for a user query or task, making retrieval a critical pre-execution safety boundary. Unlike document retr…
Aligning Human Sense: Calibrated Distributional Reward Learning for Video Generation
Nai-Xin Zhai, Weihua Cheng, Dexu Yu +9
Video generation is central to AI-powered content creation. Aligning generated videos with human preferences is a key criterion for evaluating generation quality. Despite significa…
SkillAudit: From Fixed-Suite Benchmarking to Skill-Centered Assessment
Dexu Yu, Youhua Li, Zhaoyang Guan +12
Agent skills have become a practical way to extend large language model agents, but the growing skill ecosystem still lacks a reliable way to judge whether a skill is worth deployi…
GIFT: LLM-Guided State-Reward Interface for Financial Reinforcement Learning
Yanyan Wu, Boyi Zhang, Yanlin Liu +10
Financial portfolio trading is naturally formulated as a reinforcement learning problem, where an agent sequentially rebalances assets under changing market conditions to balance r…
Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs
Jiakang Li, Guanyu Zhu, Can Jin +8
Strong reasoning depends not only on model knowledge but also on how effectively cognitive behaviors are deployed during generation. Existing methods often rely on explicit behavio…