Tom Kocmi

@kocmitom.bsky.social

Researcher at Cohere | Multilingual LLM evaluation

We'd like to officially announce the 21st iteration of the WMT General Machine Translation shared task and invite you to participate. Here is the list of main changes:

How well do LLMs handle multilinguality? 🌍🤖 🔬We brought the rigor from Machine Translation evaluation to multilingual LLM benchmarking and organized the WMT25 Multilingual Instruction Shared Task spanning 30 languages and 5 subtasks.

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🚩Machine Translation is far from “solved” - the test sets just got too easy. 🚩 Yes, the systems are much stronger. But the other half of the story is that test sets haven’t kept up. It’s no longer enough to just take a random news article and expect systems to stumble.

Stefano@sted19.bsky.social · 11mo ago

Our new #EMNLP2025 paper is out: "Estimating Machine Translation Difficulty"! 🚀 Are today's #MachineTranslation systems flawless? When SOTA models all achieve near-perfect scores on standard benchmarks, we hit an evaluation ceiling. How can we tell their true capabilities and drive future progress?

🚀 Thrilled to share what I’ve been working on at Cohere! What began in January as a scribble in my notebook “how challenging would it be...” turned into a fully-fledged translation model that outperforms both open and closed-source systems, including long-standing MT leaders.

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📊 Preliminary ranking of WMT 2025 General Machine Translation benchmark is here! But don't draw conclusions just yet - automatic metrics are biased for techniques like metric as a reward model or MBR. The official human ranking will be part of General MT findings at WMT. arxiv.org/abs/2508.14909

Preliminary Ranking of WMT25 General Machine Translation Systems

We present the preliminary ranking of the WMT25 General Machine Translation Shared Task, in which MT systems have been evaluated using automatic metrics. As this ranking is based on automatic evaluati...

arxiv.org

Tired of messy non-replicable multilingual LLM evaluation? So were we. In our new paper, we experimentally illustrate common eval. issues and present how structured evaluation design, transparent reporting, and meta-evaluation can help us to build stronger models.

Julia Kreutzer@juliakreutzer.bsky.social · last yr.

📖New preprint with Eleftheria Briakou @swetaagrawal.bsky.social @mziizm.bsky.social @kocmitom.bsky.social! arxiv.org/abs/2504.11829 🌍It reflects experiences from my personal research journey: coming from MT into multilingual LLM research I missed reliable evaluations and evaluation research…

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☀️ Summer internship at Cohere! Are you excited about multilingual evaluation, human judgment, or meta-eval? Come help us explore how a rigorous eval really looks like while questioning the status quo in LLM evaluation. I’m looking for an intern (EU timezone preferred), are you interested? Ping me!

AI is evolving fast, and Aya Vision is proof of that. This open-weights model is designed to make LLM more powerful across languages and modalities, especially vision! Can’t wait to see the real-world applications, perhaps at WMT this year 😇

Cohere Labs@cohereforai.bsky.social · last yr.

We hope Aya enables researchers and developers throughout the world to build upon this technology, ask deeper questions about multilingual AI, and develop tools that can support their communities. Learn more: cohere.com/blog/aya-vis...

Huge shoutout to colleagues at Google & Unbabel for extending our WMT24 testset to 55 languages in four domains, this is game changer! 🚀 I really hope it puts the final nail in the coffin of FLORES or WMT14. The field is evolving, legacy testsets can't show your progress arxiv.org/abs/2502.124...

WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects

As large language models (LLM) become more and more capable in languages other than English, it is important to collect benchmark datasets in order to evaluate their multilingual performance, includin...

arxiv.org

Guess what? The jubilee 🎉 20th iteration of WMT General MT 🎉 is here, and we want you to participate - as the entry barrier to make an impact is so low! This isn’t just any repeat. We’ve kept what worked, removed what was outdated, and introduced many exciting new twists! Among the key changes are:

Exciting time at this year's WMT24 General MT Shared Task: 🚀 Participant numbers increased by over 50%! 🏗️ Decoder-only architectures are leading the way. 🔊 We've introduced a new speech audio modality domain. 🌐 Online systems are losing ground to LLMs.

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