18 papers
Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation
Ziyun Xu, Bosen Ding, Yue Zhang +10
Industrial recommendation systems predominantly adopt a passive ranking paradigm that infers user preferences from implicit behavioral signals (e.g., clicks, dwell time) rather tha…
Learning User-Aware Recall: Personalized Retrieval in Long-Term Conversational Memory
ZhiShu Jiang, Haibo Liu, Xin Shen +6
Long-term conversational agents are expected to remember past interactions, but memory is useful only when the right evidence is recalled for the right user. Existing memory-augmen…
MapAgent: An Industrial-Grade Agentic Framework for City-scale Lane-level Map Generation
Deguo Xia, Zihan Li, Haochen Zhao +6
Lane-level maps are critical infrastructure for autonomous driving and lane-level navigation, yet constructing and maintaining standardized lane networks for hundreds of cities rem…
Woodpecker Distillation: Weak Models Diagnose Reasoning Bugs in Strong Models
Dayu Wang, Jiaye Yang, Weikang Li +4
Large language models often fail on reasoning tasks despite possessing the capability to solve them. We argue that many such failures arise from localized reasoning bugs in interme…
One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents
Zhaoxi Zhang, Yitong Duan, Yanzhi Zhang +9
Locating files and functions requiring modification in large software repositories is challenging due to their scale and structural complexity. Existing LLM-based methods typically…
RepoZero: Can LLMs Generate a Code Repository from Scratch?
Zhaoxi Zhang, Yiming Xu, Jiahui Liang +7
Large Language Models (LLMs) have recently shown remarkable progress in code generation, yet their ability to construct complete software repositories from scratch remains poorly u…