1 citations · 1 across the 8 of their papers we have counts for
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PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents
Yiqi Wang, Jiaqi Liu, Jiaqi Zhang +4
LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons. Existing methods provide limited support for handling memories that be…
Self-Confirming Superposition Traps in Reinforcement Learning
Dai Shi, Andi Han, Feng Chen +3
Reinforcement learning (RL) trains representations on data selected by the agent's policy, which then uses the resulting returns to guide its next choices. We show that this loop c…
ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning
Jingwei Song, Meng Chen, Jie Xiao +15
Reinforcement learning (RL) is a critical stage in post-training large language models (LLMs), involving repeated interaction between rollout generation, reward evaluation, and cen…
NeuroTTT: Bridging Pretraining-Downstream Task Misalignment in EEG Foundation Models via Test-Time Training
Suli Wang, Yangshen Deng, Zhenghua Bao +2
Large-scale foundation models for EEG signals offer a promising path to generalizable brain-computer interface (BCI) applications, but they often suffer from misalignment between p…