1 citations · 2 across the 4 of their papers we have counts for
5 papers
Can Agents Forget When Asked? A Benchmark for Memory Unlearning in LLM Agents
Bofan Xie, Chaokun Wang, Guanchen Ge +4
Long-term memory has become a core component of large language model (LLM) agents. As agents accumulate personal information over long-term use, users increasingly ask them to dele…
Gradients Know What Outcomes Don't: Unlocking Reinforcement Learning for LLM Reasoning with Gradient-Aligned Rewards
Leqi Zheng, Jinbo Su, Fang Niu +8
Reinforcement learning from verifiable rewards (RLVR) drives chain-of-thought reasoning in large language models, yet its binary outcome reward cannot distinguish among correct tra…
SciLENS: RL-Driven Autonomous Agents for Scientific Localized Evidence Navigation and Synthesis
Leqi Zheng, Jinbo Su, Yuying Li +10
Scientific literature synthesis agents increasingly rely on proprietary online services, limiting reproducibility, privacy, and offline deployment. To address this challenge, we in…
What Should I Cite? A RAG Benchmark for Academic Citation Prediction
Leqi Zheng, Jiajun Zhang, Canzhi Chen +13
With the rapid growth of Web-based academic publications, more and more papers are being published annually, making it increasingly difficult to find relevant prior work. Citation…
rLLM: Relational Table Learning with LLMs
Weichen Li, Xiaotong Huang, Jianwu Zheng +4
We introduce rLLM (relationLLM), a PyTorch library designed for Relational Table Learning (RTL) with Large Language Models (LLMs). The core idea is to decompose state-of-the-art Gr…