We establish new bounds on the Grothendieck constant $K_G$: \[ \frac{6\pi}{11} \le K_G \le \frac{\pi}{2\log(1+\sqrt2)} - 10^{-4}. \] Methodologically, our lower bound approach differs from previous works by establishing limitations on the asymptotically optimal Krivine schemes, rather than giving explicit constructions...
Rahul Saha, Alan Li, Anton Xue et al.· 5 citations· ⚡1
This work investigates whether hybrid backbones can become effective DLMs by adapting Qwen3.5 at 0.8B, 2B, 4B, and 9B scales, and finds that they can be efficient starting points for adaptation.
Anton Xue, Litu Rout, Aditya Akella et al.· 0 citations
In an important recent work, Blanc (2026) gave an algorithm for robustly learning Boolean concept classes with respect to a fixed distribution that outputs a (randomized) classifier achieving the optimal error of $\eta + \varepsilon$ where $\eta$ is the noise rate. In contrast, it is well known that deterministic hypot...
Adam R. Klivans, Konstantinos Stavropoulos, S. Tikhonov et al.· 0 citations
A smoothed-analysis framework that requires a learner to compete only with the best classifier that is robust to small random Gaussian perturbation is introduced, and the first algorithm for agnostic learning intersections of halfspaces in time is obtained, where $γ$ is the margin parameter.
Gautam Chandrasekaran, Adam R. Klivans, Vasilis Kontonis et al.· Annual Conference Computatio...· 15 citations· ⚡1
This work observes that MDLM generation involves two decisions at each step: what tokens to place at each masked position and which positions to remask, and formalizes this as a two-stage action MDP, showing that the policy gradient naturally decomposes into a token term and a masking term.
Haran Raajesh, Kulin Shah, Adam R. Klivans et al.· 1 citation
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