5 citations · 24 across the 91 of their papers we have counts for
6 papers · 1 filter
Capability Scaling-Down Laws for LLM Compression
Xueqi Cheng, Liang Wu, Kelly Wan +2
LLM compression reduces inference costs and memory requirements, but selecting a method and configuration remains largely empirical because comparable resource reductions can produ…
SAW: Stage-Aware Dynamic Weighting for Multi-Objective Reinforcement Learning in Large Language Models
Yuchen He, Baolong Bi, Shenghua Liu +7
Although multi-objective reinforcement learning (MORL) is central to aligning large language models with complex human preferences, the prevailing practice of static weighted summa…
When and Why Grouping Attention Heads Accelerates Muon Optimization
Hongtao Zhang, Wenjie Zhou, Wei Chen +1
Muon orthogonalizes matrix updates, but multi-head attention naturally operates at the level of heads. This granularity mismatch raises the question of whether Muon should be appli…
Look Globally and Reason: Two-stage Path Reasoning over Sparse Knowledge Graphs
Saiping Guan, Jiyao Wei, Xiaolong Jin +2
Sparse Knowledge Graphs (KGs), frequently encountered in real-world applications, contain fewer facts in the form of (head entity, relation, tail entity) compared to more populated…
Selective Temporal Knowledge Graph Reasoning
Zhongni Hou, Xiaolong Jin, Zixuan Li +3
Temporal Knowledge Graph (TKG), which characterizes temporally evolving facts in the form of (subject, relation, object, timestamp), has attracted much attention recently. TKG reas…
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
Zixuan Li, Yutao Zeng, Yuxin Zuo +14
In this paper, we propose KnowCoder, a Large Language Model (LLM) to conduct Universal Information Extraction (UIE) via code generation. KnowCoder aims to develop a kind of unified…