13 papers
Training Agents to Evolve with Their Harness: TaoLive Digital Avatar Agent Technical Report
TaoLive AIGC LLM Team, Yuhan Sun, Wenhao Lin +7
AI-powered digital avatar streamers must answer product questions, engage viewers, and execute marketing strategies in real time, demanding low latency, frequent strategy updates,…
DocClaw: A Unified Agentic System for Intelligent Document Processing
Siqi Xiang, Zhipeng Xu, Yufei Liu +6
Intelligent document processing (IDP) encompasses a broad range of tasks, including optical character recognition (OCR), document question answering (DocQA), and key information ex…
Enhancing Large Multimodal Models in Key Information Extraction via Scene-Aware Document Synthesis
Zhipeng Xu, Zulong Chen, Qing Liu +6
Key Information Extraction (KIE) converts visually rich documents into structured data, but practical deployment remains challenging: strong performance often relies on costly on-s…
Memory Shot for Long-Term Dialogue
Chunyi Peng, Haidong Xin, Xuanshuo Sheng +7
Large Language Models (LLMs) have demonstrated strong capabilities in general conversation, instruction following, and complex reasoning. However, in long-term dialogue settings, t…
Multi-domain Multi-modal Document Classification Benchmark with a Multi-level Taxonomy
Denghao Ma, Qing Liu, Zulong Chen +5
Document classification forms the backbone of modern enterprise content management, yet existing benchmarks remain trapped in oversimplified paradigms -- single domain settings wit…
DocScope: Benchmarking Verifiable Reasoning for Trustworthy Long-Document Understanding
Xiang Feng, Jiawei Zhou, Zhangfeng Huang +6
Evaluating whether Multimodal Large Language Models can produce trustworthy, verifiable reasoning over long, visually rich documents requires evaluation beyond end-to-end answer ac…
CC-OCR V2: Fine-Grained Attribution of LMM Failures in Real-World Visual Document Understanding
Chunyi Peng, Zhipeng Xu, Yuqi Xiong +12
Recent Large Multimodal Models (LMMs) have achieved remarkable progress on OCR-centric document understanding and processing tasks. Existing benchmarks primarily evaluate LMMs acro…
ReAlign: Optimizing the Visual Document Retriever with Reasoning-Guided Fine-Grained Alignment
Hao Yang, Yifan Ji, Zhipeng Xu +6
Visual document retrieval aims to retrieve a set of document pages relevant to a query from visually rich collections. Existing methods often employ Vision-Language Models (VLMs) t…
Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains
Yuqi Xiong, Chunyi Peng, Zhipeng Xu +6
Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a given query. Existing VRAG frameworks us…
UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents
Yifan Ji, Zhipeng Xu, Zhenghao Liu +7
Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual quality, and task-specific information req…
Teaching LLMs to Learn Tool Trialing and Execution through Environment Interaction
Xingjie Gao, Pengcheng Huang, Zhenghao Liu +6
Equipping Large Language Models (LLMs) with external tools enables them to solve complex real-world problems. However, the robustness of existing methods remains a critical challen…
Long-Chain Reasoning Distillation via Adaptive Prefix Alignment
Zhenghao Liu, Zhuoyang Wu, Xinze Li +6
Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in solving complex mathematical problems. Recent studies show that distilling long re…
Empirical Analysis of Decoding Biases in Masked Diffusion Models
Pengcheng Huang, Tianming Liu, Zhenghao Liu +5
Masked Diffusion Models (MDMs) have recently emerged as a promising non-autoregressive paradigm for sequence generation. However, their performance is highly sensitive to the choic…