7 papers
NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation
Jinhang Xu, Qiyuan Zhu, Yujun Wu +11
LLM-powered multi-agent systems can now automate the full research pipeline from ideation to paper writing, but a fundamental question remains: automation for whom? Researchers ope…
KGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning
Yisen Gao, Jiaxin Bai, Haoyu Huang +5
Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure. However, most existing meth…
DC-W2S: Dual-Consensus Weak-to-Strong Training for Reliable Process Reward Modeling in Biological Reasoning
Chi-Min Chan, Ehsan Hajiramezanali, Xiner Li +6
In scientific reasoning tasks, the veracity of the reasoning process is as critical as the final outcome. While Process Reward Models (PRMs) offer a solution to the coarse-grained…
Unlocking Data Value in Finance: A Study on Distillation and Difficulty-Aware Training
Chuxue Cao, Honglin Lin, Zhanping Zhong +5
Large Language Models (LLMs) have demonstrated strong general capabilities, yet their deployment in finance remains challenging due to dense domain-specific terminology, stringent…
GSPR: Aligning LLM Safeguards as Generalizable Safety Policy Reasoners
Haoran Li, Yulin Chen, Jingru Zeng +7
As large language models (LLMs) are increasingly integrated into numerous applications across various domains, LLMs' safety becomes a critical concern for both application develope…
Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning
Wenbin Hu, Haoran Li, Huihao Jing +7
While Large Language Models (LLMs) exhibit remarkable capabilities, they also introduce significant safety and privacy risks. Current mitigation strategies often fail to preserve c…