Fashion

[Submitted on 21 Oct 2024 (v1), last revised 24 Feb 2026 (this version, v5)] View a PDF of the paper titled Statistical Inference for Temporal Difference Learning with Linear Function Approximation, by Weichen Wu and 3 other authors View PDF Abstract:We investigate the statistical properties of Temporal Difference (TD) learning with Polyak-Ruppert averaging, arguably one of the most widely used …

[Submitted on 11 Jan 2026 (v1), last revised 23 Feb 2026 (this version, v3)] View a PDF of the paper titled Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching, by Stephen Gadd View PDF Abstract:Linking names across historical sources, languages, and writing systems remains a fundamental challenge in digital humanities and geographic information retrieval. Existing approaches require language-specific phonetic algorithms …

With OpenAI on the verge of finalizing a new $100 billion round, and Anthropic just closing its own monster $30 billion raise, one thing is clear: The concept of investor “loyalty” is only hanging on by a thread.  At least a dozen direct investors in OpenAI were announced as backers in Anthropic’s $30 billion raise earlier this month, including Founders …

this past month, a social network run entirely by AI agents was the most fascinating experiment on the internet. In case you haven’t heard of it, Moltbook is essentially a social network platform for agents. Bots post, reply, and interact without human intervention. And for a few days, it seemed to be all anyone could talk about — with autonomous agents forming …

OpenAI CEO Sam Altman addressed concerns about AI’s environmental impact this week while speaking at an event hosted by The Indian Express. For one thing, Altman — who was in India for a major AI summit — said concerns about AI’s water usage are “totally fake,” though he acknowledged it was a real issue when “we used to do evaporative …

[Submitted on 21 Mar 2025 (v1), last revised 19 Feb 2026 (this version, v2)] View a PDF of the paper titled Capturing Individual Human Preferences with Reward Features, by Andr\’e Barreto and 8 other authors View PDF HTML (experimental) Abstract:Reinforcement learning from human feedback usually models preferences using a reward function that does not distinguish between people. We argue that …

[Submitted on 17 Feb 2026 (v1), last revised 18 Feb 2026 (this version, v2)] Authors:Shiqi Liu, Zeyu He, Guojian Zhan, Letian Tao, Zhilong Zheng, Jiang Wu, Yinuo Wang, Yang Guan, Kehua Sheng, Bo Zhang, Keqiang Li, Jingliang Duan, Shengbo Eben Li View a PDF of the paper titled STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens, by …

Startup founders are being pushed to move faster than ever, using AI while facing tighter funding, rising infrastructure costs, and more pressure to show real traction early. Cloud credits, access to GPUs, and foundation models have made it easier to get started, but those early infrastructure choices can have unforeseen consequences once startups move beyond free credits and into real …

[Submitted on 30 Sep 2025 (v1), last revised 15 Feb 2026 (this version, v2)] View a PDF of the paper titled BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses, by Xin Xu and 5 other authors View PDF HTML (experimental) Abstract:Existing studies on bias mitigation methods for large language models (LLMs) use diverse baselines and metrics to …

[Submitted on 1 Sep 2024 (v1), last revised 13 Feb 2026 (this version, v4)] View a PDF of the paper titled Generating Physical Dynamics under Priors, by Zihan Zhou and 2 other authors View PDF Abstract:Generating physically feasible dynamics in a data-driven context is challenging, especially when adhering to physical priors expressed in specific equations or formulas. Existing methodologies often …