9 papers
CHILL-Harness: Counterfactual Harness Learning for Efficient Reasoning in Long-Horizon Agents
Jiarun Fu, Lizhong Ding, Sida Chen +6
Agent harnesses have become the operational infrastructure of modern large language model agents, coordinating context, tools, verification, and execution control to translate late…
StreamTGN: A GPU-Efficient Serving System for Streaming Temporal Graph Neural Networks
Lingling Zhang, Pengpeng Qiao, Zhiwei Zhang +2
Temporal Graph Neural Networks (TGNs) achieve state-of-the-art performance on dynamic graph tasks, yet existing systems focus exclusively on accelerating training -- at inference t…
Astro: Activation-guided Structured Regularization for Outlier-Robust LLM Post-Training Quantization
Xi Chen, Ming Li, Junxi Li +5
Weight-only post-training quantization (PTQ) is crucial for efficient Large Language Model (LLM) deployment but suffers from accuracy degradation caused by weight and activation ou…
Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
Xi Chen, Kaituo Feng, Changsheng Li +4
Low-rank training has emerged as a promising approach for reducing memory usage in training Large Language Models (LLMs). Previous methods either rely on decomposing weight matrice…
Graph-Based Feature Augmentation for Predictive Tasks on Relational Datasets
Lianpeng Qiao, Ziqi Cao, Kaiyu Feng +2
Data has become a foundational asset driving innovation across domains such as finance, healthcare, and e-commerce. In these areas, predictive modeling over relational tables is co…
DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations
Yuhan Guo, Lizhong Ding, Shihan Jia +6
Explainable AI (XAI) builds trust in complex systems through model attribution methods that reveal the decision rationale. However, due to the absence of a unified optimal explanat…