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Reposted by Siqi Liu (刘思奇)

Kaggle @kaggle.com · 29/01/2026

📌 Mark Your Calendar: Live Game Arena Event This Monday! We are releasing two new games, Poker and Werewolf, along with an updated Chess leaderboard next Monday, February 2, running daily from 9:30 AM PT to 11:30 AM PT through February 4

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Siqi Liu (刘思奇) @liusiqi.bsky.social · 27/09/2025

We have got exciting (and unconventional) stuff cooking and we are hiring for a strong research engineer on the GDM Game Theory team in London. Consider apply if you are interested in the intersection of game theory, multiagent systems and LLMs! job-boards.greenhouse.io/deepmind/job...

job-boards.greenhouse.io

Research Engineer, Game Theory & Multi-Agent Systems

London, UK

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Siqi Liu (刘思奇) @liusiqi.bsky.social · 18/04/2025

Frontier models are often compared on crowdsourced user prompts - user prompts can be low-quality, biased and redundant, making "performance on average" hard to trust. Come find us at #ICLR2025 to discuss game-theoretic evaluation (shorturl.at/0QtBj)! See you in Singapore!

shorturl.at

Re-evaluating Open-Ended Evaluation of Large Language Models

A case study using the livebench.ai leaderboard.

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Reposted by Siqi Liu (刘思奇)

Luke Marris @lukemarris.bsky.social · 17/04/2025

[🧵1/N] Thrilled to share our work "Re-evaluating Open-Ended Evaluation of Large Language Models"! 🚀 Popular LLM leaderboards (think Elo/Chatbot Arena) are useful, but are they telling the whole story? We find issues w/ redundancy & bias. 🤔 Paper @ ICLR 2025: arxiv.org/abs/2502.20170 #LLM #ICLR2025

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Reposted by Siqi Liu (刘思奇)

Jeff Dean @jeffdean.bsky.social · 25/03/2025

🥁Introducing Gemini 2.5, our most intelligent model with impressive capabilities in advanced reasoning and coding. Now integrating thinking capabilities, 2.5 Pro Experimental is our most performant Gemini model yet. It’s #1 on the LM Arena leaderboard. 🥇

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Reposted by Siqi Liu (刘思奇)

Luke Marris @lukemarris.bsky.social · 18/02/2025

[🧵1/N] Please check out our new paper (arxiv.org/abs/2502.11645) on game-theoretic evaluation. It is the first method that results in clone-invariant ratings in N-player, general-sum interactions. Co-authors: @liusiqi.bsky.social , Ian Gemp, Georgios Piliouras, @sharky6000.bsky.social 🎉

arxiv.org

Deviation Ratings: A General, Clone-Invariant Rating Method

Many real-world multi-agent or multi-task evaluation scenarios can be naturally modelled as normal-form games due to inherent strategic (adversarial, cooperative, and mixed motive) interactions. These...

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