406 citations · 1.8k across the 130 of their papers we have counts for
4 papers · 1 filter
AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning
Zhiheng Xi, Jixuan Huang, Chenyang Liao +20
Developing autonomous LLM agents capable of making a series of intelligent decisions to solve complex, real-world tasks is a fast-evolving frontier. Like human cognitive developmen…
Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders
Zhengfu He, Wentao Shu, Xuyang Ge +9
Sparse Autoencoders (SAEs) have emerged as a powerful unsupervised method for extracting sparse representations from language models, yet scalable training remains a significant ch…
ModelLock: Locking Your Model With a Spell
Yifeng Gao, Yuhua Sun, Xingjun Ma +2
This paper presents a novel model protection paradigm ModelLock that locks (destroys) the performance of a model on normal clean data so as to make it unusable or unextractable wit…
Robust Optimization as Data Augmentation for Large-scale Graphs
Kezhi Kong, Guohao Li, Mucong Ding +5
Data augmentation helps neural networks generalize better by enlarging the training set, but it remains an open question how to effectively augment graph data to enhance the perfor…