11 papers
Deep Search with Hierarchical Meta-Cognitive Monitoring Inspired by Cognitive Neuroscience
Zhongxiang Sun, Qipeng Wang, Weijie Yu +3
Deep search agents powered by large language models have demonstrated strong capabilities in multi-step retrieval, reasoning, and long-horizon task execution. However, their practi…
When Personalization Misleads: Understanding and Mitigating Hallucinations in Personalized LLMs
Zhongxiang Sun, Yi Zhan, Chenglei Shen +4
Personalized large language models (LLMs) adapt model behavior to individual users to enhance user satisfaction, yet personalization can inadvertently distort factual reasoning. We…
Searching in Space and Time: Unified Memory-Action Loops for Open-World Object Retrieval
Taijing Chen, Sateesh Kumar, Junhong Xu +3
Service robots must retrieve objects in dynamic, open-world settings where requests may reference attributes ("the red mug"), spatial context ("the mug on the table"), or past stat…
PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization
Kepu Zhang, Teng Shi, Weijie Yu +1
Personalized retrieval-augmented generation (RAG) aims to produce user-tailored responses by incorporating retrieved user profiles alongside the input query. Existing methods prima…
Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search
Weicong Qin, Yi Xu, Weijie Yu +6
Personalized search systems in e-commerce platforms increasingly involve user interactions with AI assistants, where users consult about products, usage scenarios, and more. Levera…
An Explicit Syllogistic Legal Reasoning Framework for Large Language Models
Kepu Zhang, Weijie Yu, Zhongxiang Sun +1
Syllogistic reasoning is crucial for sound legal decision-making, allowing legal professionals to draw logical conclusions by applying general principles to specific case facts. Wh…