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Daniel Kang
608 posts
@ddkang

Daniel Kang

@ddkang
Distinguished AI research scientist at Bridgewater AIA labs, asst. professor at UIUC CS. Formerly in the Stanford DAWN lab and the Berkeley Sky Lab.
New York, NY
ddkang.github.io
Joined November 2010
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  • @ddkang
    Daniel Kang
    @ddkang
    Aug 27
    New research from Bridgewater AIA Labs and UIUC, in collaboration with Thinking Machines! We use @tinkerapi to achieve state-of-the-art on a cleaned version of the BIRD text-to-SQL dataset, outperforming all frontier models we tested (including Fable and Sol) up to 8x cheaper.
    @tinkerapi
    Tinker
    Thinking Machines
    @tinkerapi
    Aug 27
    LLMs with scaffolds have lagged on text-to-SQL, a task that relies on human judgment. By folding expert judgment into every part of RLVR on Tinker, @maxYuxuanZhu and @ddkang (UIUC and Bridgwater) trained the first text-to-SQL model to beat the human mark. thinkingmachines.ai/news/putting-t…
    5
  • @ddkang
    Daniel Kang
    @ddkang
    Jul 27
    Building text-to-SQL agents? Don’t blindly trust benchmarks/leaderboards. In our VLDB 2026 paper, we find >50% annotation error rates in BIRD and Spider 2.0-Snow, two widely used text-to-SQL benchmarks, shifting agents’ measured performance by up to 19%. 1/9
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  • @ddkang
    Daniel Kang
    @ddkang
    Jul 20
    New research from Bridgewater AIA Labs, UIUC, and MIT: we prove what we believe to be the first non-vacuous generalization bounds for reasoning LLMs on real-world problems. RLVR powers frontier reasoning capabilities yet its generalization to unseen data has remained an open
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  • @ddkang
    Daniel Kang
    @ddkang
    Jul 5
    Anyone know the best place to watch the US game in Seoul?
    1
  • @ddkang
    Daniel Kang
    @ddkang
    Jul 1
    This is a good time to mention that I've joined Bridgewater AIA Labs, with the goal of training the best financial models. I'll also be at ICML 🇰🇷! Reach out if you're interested in chatting, DMs open :)
    @ddkang
    Daniel Kang
    @ddkang
    Jun 30
    New research from Bridgewater AIA Labs and @thinkymachines! We show that high quality investor taste is critical for high performance across several investor workflow tasks. Our results point towards a world where organizational expertise leads to models with differentiated
    5
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