{"slug":"multimodal-document","label":"Multimodal Document","item_count":3,"day_count":2,"source_count":3,"first_seen":"2026-10-09T07:21:36+00:00","last_updated":"2026-10-27T09:53:21+00:00","generated_at":"2026-10-29T00:13:38.528542+00:00","sources":["arxiv_agent_systems_research","arxiv_cs_ai","arxiv_cs_cl"],"days":[{"date":"2026-10-09","items":[{"title":"Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QA","url":"http://arxiv.org/abs/2610.13128v1","source":"arxiv_cs_ai","type":"paper","summary_1line":"Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-augmented agents give one model both kinds of tools and let it sc...","why_it_matters":"Matches feed focus: agent, eval.","sid":"fd7cd167364e497d","published":"2026-10-09T07:21:36+00:00","editor_note":"First paper: gives locating and reading separate role-specialized tool agents over a knowledge-point index."}]},{"date":"2026-10-27","items":[{"title":"RouteDRAG: Learning to Route and Control Agentic Execution for Multimodal Document RAG","url":"http://arxiv.org/abs/2610.36444v1","source":"arxiv_agent_systems_research","type":"paper","summary_1line":"Web-based applications increasingly rely on understanding long multimodal documents, where answering questions often requires combining information across pages, tables, and figures. Agentic retrieval-augmented genera...","why_it_matters":"Matches feed focus: agentic, eval.","sid":"9ab63498f33996c4","published":"2026-10-27T00:45:49+00:00","editor_note":"Adds learned routing and execution control to agentic multimodal document RAG."},{"title":"DocXEval: A Systematic Evaluation of Explainability in Multimodal Document Understanding","url":"http://arxiv.org/abs/2610.36929v1","source":"arxiv_cs_cl","type":"paper","summary_1line":"Multimodal transformer models have driven unprecedented performance breakthroughs in modern document understanding. However, the inherent black-box nature of these models remains a major obstacle to their safe deploym...","why_it_matters":"Matches feed focus: evaluation.","sid":"52897c76c61a9c65","published":"2026-10-27T09:53:21+00:00","editor_note":"Shifts focus from accuracy to explainability evaluation of multimodal document understanding."}]}],"editorial":{"tldr":"An Oct 9 arXiv paper split multimodal document QA agents into role-specialized locate, judge and read tools over a knowledge-point index. Until Oct 27, no follow-up appeared in the feed.","stale":false,"whats_new":"Two Oct 27 papers extend the thread: RouteDRAG learns to route and control agentic execution for multimodal document RAG, and DocXEval benchmarks explainability in document understanding models.","why_it_matters":"Document-QA agents are moving from one generalist tool-using model toward routed, role-specific stages, and explainability is now being measured separately from accuracy.","take_for_builders":"Keep retrieval and reading as separate, individually evaluable stages in document-QA pipelines, and wait for released code or shared benchmarks before replacing a working setup with these preprints.","status":{"state":"Developing","tone":"rising","changed":"2026-10-27","detail":"Three arXiv preprints, no production releases: agent architecture for multimodal document RAG is converging on routing, while explainability evaluation lags.","track":[{"label":"role-specialized agents","detail":"Oct 9","tone":"launch","weight":40},{"label":"routing + explainability","detail":"Oct 27 → now","tone":"now","weight":60}]},"beats":[{"kicker":"ARCHITECTURE","tone":"launch","headline":"Role-specialized tool agents split locating from reading","summary":"Separates retrieval tools from reading tools instead of giving one model both.","sids":["fd7cd167364e497d"]},{"kicker":"ROUTING","tone":"rising","headline":"RouteDRAG learns to route and control agentic execution","summary":"Targets questions that need combining pages, tables and figures.","sids":["9ab63498f33996c4"]},{"kicker":"NOW","tone":"now","headline":"DocXEval evaluates explainability of document models","summary":"Addresses the black-box obstacle to safe deployment of multimodal document models.","sids":["52897c76c61a9c65"]}],"open_questions":["Do RouteDRAG or the locate-judge-read agents publish code or benchmark numbers on a shared multimodal document QA set?","Does any production document-QA product adopt routed or role-specialized retrieval and reading stages?","Do later papers report DocXEval explainability scores for the agentic RAG systems in this thread?"],"generated_at":"2026-10-29T00:30:00+00:00"}}