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On-line Learning in Tree MDPs by Treating Policies as Bandit Arms

cs.AI · 2026-05-06 · unverdicted · novelty 7.0

Bandit algorithms can be adapted to Tree MDPs by treating policies as arms with shared-data confidence bounds, achieving polynomial memory and instance-dependent bounds on sample complexity and regret that depend on terminal-state gaps rather than all policies.

Towards AI-assisted Neutrino Flavor Theory Design

hep-ph · 2025-06-09 · unverdicted · novelty 7.0

AMBer applies reinforcement learning with physics feedback to automate construction of neutrino flavor models that minimize free parameters, validated on known cases and extended to a new symmetry group.

Parametric Open Source Games

cs.GT · 2026-06-25 · unverdicted · novelty 6.0

Introduces parametric open-source games as continuous analogues of program equilibria, proves equilibrium existence, and derives an exact coupling threshold for cooperation in symmetric 2x2 games under gradient ascent.

Improved bounds for the double cap conjecture

math.CO · 2026-05-27 · unverdicted · novelty 6.0

Improved upper bound α_3 ≤ 0.2953 for Witsenhausen's problem in dimension 3 via harmonic analysis, geometric fractional chromatic number, and a computer-searched 33-point set.

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders

cs.RO · 2026-05-19 · accept · novelty 6.0 · 2 refs

ARC-RL is a new suite of four MuJoCo continuous-control environments featuring game-inspired hexapod and quadruped morphologies, a single closed-form multi-component reward function, CPG demonstrators, and empirical comparisons of online and offline-to-online RL algorithms.

Evaluation-driven Scaling for Scientific Discovery

cs.LG · 2026-04-21 · unverdicted · novelty 6.0

SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.

Language Models (Mostly) Know What They Know

cs.CL · 2022-07-11 · unverdicted · novelty 6.0

Language models show good calibration when asked to estimate the probability that their own answers are correct, with performance improving as models get larger.

Scaling Laws for Transfer

cs.LG · 2021-02-02 · unverdicted · novelty 6.0

Effective data transferred from pre-training to fine-tuning is described by a power law in model parameter count and fine-tuning dataset size, acting like a multiplier on the fine-tuning data.

VET: A Framework for Analyzing AI Discourse

cs.AI · 2026-06-01 · unverdicted · novelty 5.0

Introduces the VET framework to categorize and critique polarized AI narratives including hype, doom, denial, and normalcy.

Scheduling Discovery in the 2020s

astro-ph.IM · 2019-07-17 · unverdicted · novelty 2.0

Advocates developing high-quality open-source scheduling software and linking observation planning with data analysis for future astronomical surveys.

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  • Improved bounds for the double cap conjecture math.CO · 2026-05-27 · unverdicted · none · ref 14

    Improved upper bound α_3 ≤ 0.2953 for Witsenhausen's problem in dimension 3 via harmonic analysis, geometric fractional chromatic number, and a computer-searched 33-point set.