2 citations · 3 across the 14 of their papers we have counts for
15 papers
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning
Yaorui Shi, Yuxin Chen, Zhengxi Lu +6
A persistent skill library allows language model agents to reuse successful strategies across tasks. Maintaining such a library requires three coupled capabilities. The agent selec…
Joint Optimization of Multi-agent Memory System
Wenyu Mao, Haoyang Liu, Haosong Tan +4
Memory systems are critical for LLMs, mitigating context window limitations and supporting long-horizon user-LLM interactions. Such systems typically comprise multiple agents respo…
MiniOneRec: An Open-Source Framework for Scaling Generative Recommendation
Xiaoyu Kong, Leheng Sheng, Junfei Tan +5
The recent success of large language models (LLMs) has renewed interest in whether recommender systems can achieve similar scaling benefits. Conventional recommenders, dominated by…
Reinforced Preference Optimization for Recommendation
Junfei Tan, Yuxin Chen, An Zhang +7
Recent breakthroughs in large language models (LLMs) have fundamentally shifted recommender systems from discriminative to generative paradigms, where user behavior modeling is ach…
Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation
Guoqing Hu, An Zhang. Shuchang Liu, Wenyu Mao +7
Recommenders aim to rank items from a discrete item corpus in line with user interests, yet suffer from extremely sparse user preference data. Recent advances in diffusion models h…
bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
Wence Ji, Jiancan Wu, Aiying Li +5
With the rapid advancement of large language models (LLMs), their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically impor…
Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents
Yaorui Shi, Yuxin Chen, Siyuan Wang +5
Large language models face challenges in long-context question answering, where key evidence of a query may be dispersed across millions of tokens. Existing works equip large langu…
Quantile Advantage Estimation: Stabilizing RLVR for LLM Reasoning
Junkang Wu, Kexin Huang, Jiancan Wu +3
Reinforcement Learning with Verifiable Rewards (RLVR) strengthens LLM reasoning, but training often oscillates between {entropy collapse} and {entropy explosion}. We trace both haz…
Denoising Neural Reranker for Recommender Systems
Wenyu Mao, Shuchang Liu, Hailan Yang +9
For multi-stage recommenders in industry, a user request would first trigger a simple and efficient retriever module that selects and ranks a list of relevant items, then the recom…
SafeSieve: From Heuristics to Experience in Progressive Pruning for LLM-based Multi-Agent Communication
Ruijia Zhang, Xinyan Zhao, Ruixiang Wang +5
LLM-based multi-agent systems exhibit strong collaborative capabilities but often suffer from redundant communication and excessive token overhead. Existing methods typically enhan…
Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning
Yaorui Shi, Sihang Li, Chang Wu +5
Large language models have demonstrated impressive reasoning capabilities but are inherently limited by their knowledge reservoir. Retrieval-augmented reasoning mitigates this limi…
SafeMLRM: Demystifying Safety in Multi-modal Large Reasoning Models
Junfeng Fang, Yukai Wang, Ruipeng Wang +5
The rapid advancement of multi-modal large reasoning models (MLRMs) -- enhanced versions of multimodal language models (MLLMs) equipped with reasoning capabilities -- has revolutio…
Neuron-Level Sequential Editing for Large Language Models
Houcheng Jiang, Junfeng Fang, Tianyu Zhang +4
This work explores sequential model editing in large language models (LLMs), a critical task that involves modifying internal knowledge within LLMs continuously through multi-round…
Text-guided Diffusion Model for 3D Molecule Generation
Yanchen Luo, Junfeng Fang, Sihang Li +5
The de novo generation of molecules with targeted properties is crucial in biology, chemistry, and drug discovery. Current generative models are limited to using single property va…
LaMP-Val: Large Language Models Empower Personalized Valuation in Auction
Jie Sun, Tianyu Zhang, Houcheng Jiang +11
Auctions are a vital economic mechanism used to determine the market value of goods or services through competitive bidding within a specific framework. However, much of the curren…