13 citations · 14 across the 11 of their papers we have counts for
5 papers · 1 filter
Activation Compression in LLMs: Theoretical Analysis and Efficient Algorithm
Wen-Da Wei, Han-Bin Fang, Yang-Di Liu +3
Training large language models (LLMs) is highly memory-intensive, as training must store not only weights and optimizer states but also intermediate activations for backpropagation…
Hindsight Credit Assignment for Long-Horizon LLM Agents
Hui-Ze Tan, Xiao-Wen Yang, Hao Chen +7
Large Language Model (LLM) agents often face significant credit assignment challenges in long-horizon, multi-step tasks due to sparse rewards. Existing value-free methods, such as…
Curriculum Abductive Learning
Wen-Chao Hu, Qi-Jie Li, Lin-Han Jia +4
Abductive Learning (ABL) integrates machine learning with logical reasoning in a loop: a learning model predicts symbolic concept labels from raw inputs, which are revised through…
Robust Semi-Supervised Learning in Open Environments
Lan-Zhe Guo, Lin-Han Jia, Jie-Jing Shao +1
Semi-supervised learning (SSL) aims to improve performance by exploiting unlabeled data when labels are scarce. Conventional SSL studies typically assume close environments where i…
Learning for Long-Horizon Planning via Neuro-Symbolic Abductive Imitation
Jie-Jing Shao, Hao-Ran Hao, Xiao-Wen Yang +1
Recent learning-to-imitation methods have shown promising results in planning via imitating within the observation-action space. However, their ability in open environments remains…