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Unlocking Reasoning Capability on Machine Translation in Large Language Models research paper by Cohere, 2026

Cohere · Feb 16, 2026 · Reasoning 7 months ago

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What it shows

Finds that step-by-step reasoning makes machine translation worse, then trains a model on structured draft-and-revise traces that improve it.

Summarised by hand from the abstract.

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ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent PlanningThinkAct, a dual-system framework, uses reinforced visual latent planning to enable few-shot adaptation, long-horizon planning, and self-correction in embodied AI tasks by bridging high-level reasoning with low-level action execution.NVIDIA · Jul 2025 · Unverified1 year ago172
About this paper
Authors
Sara Rajaee, Sebastian Vincent, Alexandre Berard and 3 more
arXiv
2602.14763 · PDF
Citations
Not counted yet · Semantic Scholar
Upvotes
- · Hugging Face
Lab
Cohere · on Companies · on Acquisitions · on Releases

Changes

What changed
New paperAdded to the listSep 26, 2026today

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