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cs.CV2026

LAVE: Latent Visual Evidence-Enhanced Planning for Video Tool-use Agents

Zijian Wang, Junnan Zhu, Rongzhen Li +7

Long-video understanding requires models to efficiently acquire and reuse sparse visual evidence from long and redundant video streams. Recent video tool-use agents address this ch…

cs.CV2026

ReTool-Video: Recursive Tool-Using Video Agents with Meta-Augmented Tool Grounding

Xiao Liu, Nayu Liu, Junnan Zhu +6

Video understanding requires active evidence seeking, motivating tool-augmented video agents for temporal reasoning, cross-modal understanding, and complex question answering. Exis…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…