activity
20242026
most citedSimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs

Chi Zhang, Wenxuan Ding, Jiale Liu +3

Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities on Visual-Question-Answering (VQA) benchmarks. However, their robustness against textual misinform…

cs.CV20251 cited

SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement

Chelsi Jain, Yiran Wu, Yifan Zeng +5

Document Visual Question Answering (DocVQA) is a practical yet challenging task, which is to ask questions based on documents while referring to multiple pages and different modali…

cs.MA20251 cited

Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems

Shaokun Zhang, Ming Yin, Jieyu Zhang +8

Failure attribution in LLM multi-agent systems-identifying the agent and step responsible for task failures-provides crucial clues for systems debugging but remains underexplored a…

cs.CL2025

Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale

Jiale Liu, Yifan Zeng, Shaokun Zhang +5

LLM-based optimization has shown remarkable potential in enhancing agentic systems. However, the conventional approach of prompting LLM optimizer with the whole training trajectori…

cs.CL2024

Memory-Augmented Agent Training for Business Document Understanding

Jiale Liu, Yifan Zeng, Malte Højmark-Bertelsen +3

Traditional enterprises face significant challenges in processing business documents, where tasks like extracting transport references from invoices remain largely manual despite t…