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Google DeepMind

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

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  • cs.LG2
  • cs.CL1

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most citedThe FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input

3 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025

Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates

Jincheng Mei, Bo Dai, Alekh Agarwal +4

We provide a new understanding of the stochastic gradient bandit algorithm by showing that it converges to a globally optimal policy almost surely using \emph{any} constant learnin…

cs.CL2025★ 3 cited

The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input

Alon Jacovi, Andrew Wang, Chris Alberti +23

We introduce FACTS Grounding, an online leaderboard and associated benchmark that evaluates language models' ability to generate text that is factually accurate with respect to giv…

cs.LG2024

Verified Neural Compressed Sensing

Rudy Bunel, Krishnamurthy Dvijotham, M. Pawan Kumar +2

We develop the first (to the best of our knowledge) provably correct neural networks for a precise computational task, with the proof of correctness generated by an automated verif…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.