5 papers · 1 filter
ACE: Pluggable Adaptive Context Elasticizer across Agents
Ning Liao, Zihao Long, Xiaoxing Wang +6
The increasing complexity of agentic tasks has led to rapidly growing trajectory lengths, which poses significant challenges for large language model (LLM) based agents with fixed…
AutoAgent: Evolving Cognition and Elastic Memory Orchestration for Adaptive Agents
Xiaoxing Wang, Ning Liao, Shikun Wei +2
Autonomous agent frameworks still struggle to reconcile long-term experiential learning with real-time, context-sensitive decision-making. In practice, this gap appears as static c…
HELP: HyperNode Expansion and Logical Path-Guided Evidence Localization for Accurate and Efficient GraphRAG
Yuqi Huang, Ning Liao, Kai Yang +4
Large Language Models (LLMs) often struggle with inherent knowledge boundaries and hallucinations, limiting their reliability in knowledge-intensive tasks. While Retrieval-Augmente…
CircuitSeer: Mining High-Quality Data by Probing Mathematical Reasoning Circuits in LLMs
Shaobo Wang, Yongliang Miao, Yuancheng Liu +3
Large language models (LLMs) have demonstrated impressive reasoning capabilities, but scaling their performance often relies on massive reasoning datasets that are computationally…
ssToken: Self-modulated and Semantic-aware Token Selection for LLM Fine-tuning
Xiaohan Qin, Xiaoxing Wang, Ning Liao +5
Data quality plays a critical role in enhancing supervised fine-tuning (SFT) for large language models (LLMs), and token-level data selection has emerged as a promising direction f…