DeepTrans Studio: Turning Expert Interventions into Shared Team Knowledge in Agentic Translation Workflows
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Abstract (arXiv)
Professional translation is often a team-based process: translators, reviewers, and project managers must coordinate terminology, legal force, and accountability across documents. Yet many LLM-based translation tools treat human corrections as isolated edits. Expert decisions made in one segment or by one member are rarely captured as reusable knowledge for the rest of the team. We present DeepTrans Studio, a collaborative translation workspace that lets professionals intercept selected nodes in an agentic translation workflow, review evidence, revise AI outputs, and save approved decisions to a shared team memory. During the demo, attendees will role-play translators and reviewers, resolve preset terminology and legal-modal risks, and see how their decisions are propagated to downstream segments and surfaced in a teammate's workspace as reusable precedents. The demo illustrates how human interventions in AI-mediated work can become shared, traceable knowledge rather than one-off corrections.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 3 of its 8 references that are in the map. First posted on arXiv 29 Jun 2026.
Builds on
3 of 8 references.
References · 3
- 2021Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translationcited by 338
- 2022Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literaturecited by 45
- 2024Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Textscited by 31
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- 2025AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains
- 2024Towards Red Teaming in Multimodal and Multilingual Translation
- 2024(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts
- 2025DeepTrans: Deep Reasoning Translation via Reinforcement Learning
- 2024Agent AI with LangGraph: A Modular Framework for Enhancing Machine Translation Using Large Language Models
- 2025Cochain: Balancing Insufficient and Excessive Collaboration in LLM Agent Workflows