4 citations · 5 across the 12 of their papers we have counts for
7 papers · 1 filter
SWE-Stream: Scaling Executable Training Data for SWE Agents via Progressive Construction and Elastic Streaming
Chengyang Liu, Wen Yang, Shifeng Chen +5
Software engineering agents have advanced rapidly, but scaling their training remains constrained by the limited availability of high-quality executable tasks. Development historie…
Taming the Thinker: Conditional Entropy Shaping for Adaptive LLM Reasoning
Shuyu Wei, Jian Sun, Delai Qiu +6
Entropy-based deep reasoning has emerged as a promising direction for improving the reasoning capabilities of Large Language Models (LLMs), but existing methods often either increa…
LaTER: Efficient Test-Time Reasoning via Latent Exploration and Explicit Verification
Xuan Li, Yining Wang, Yuchen Liu +7
Chain-of-thought (CoT) reasoning improves large language models (LLMs) on difficult tasks, but it also makes inference expensive because every intermediate step must be generated a…
Parser-Oriented Structural Refinement for a Stable Layout Interface in Document Parsing
Fuyuan Liu, Dianyu Yu, He Ren +10
Accurate document parsing requires both robust content recognition and a stable parser interface. In explicit Document Layout Analysis (DLA) pipelines, downstream parsers do not co…
Zipper-LoRA: Dynamic Parameter Decoupling for Speech-LLM based Multilingual Speech Recognition
Yuxiang Mei, Delai Qiu, Shengping Liu +2
Speech Large Language Models (Speech-LLMs) have emerged as a powerful approach for automatic speech recognition (ASR) by aligning speech encoders with large language models. Howeve…
PARL: Position-Aware Relation Learning Network for Document Layout Analysis
Fuyuan Liu, Dianyu Yu, He Ren +10
Document layout analysis aims to detect and categorize structural elements (e.g., titles, tables, figures) in scanned or digital documents. Popular methods often rely on high-quali…
FocalOrder: Focal Preference Optimization for Reading Order Detection
Fuyuan Liu, Dianyu Yu, He Ren +10
Reading order detection is the foundation of document understanding. Most existing methods rely on uniform supervision, implicitly assuming a constant difficulty distribution acros…