arXiv:2601.07963v1 Announce Type: new Abstract: The transformative potential of 3D content creation has been progressively unlocked through advancements in generative models. Recently, intuitive drag editing with geometric changes has attracted significant attention in 2D editing yet remains challenging for 3D scenes. In this paper, we introduce 3DGS-Drag — a point-based 3D editing framework that provides efficient, intuitive drag manipulation of real 3D scenes. Our approach bridges the gap between deformation-based and 2D-editing-based 3D editing methods, addressing their limitations […]

Ver mais

arXiv:2603.05578v1 Announce Type: new Abstract: Research on self-evolving language agents has accelerated, drawing increasing attention to their ability to create, adapt, and maintain tools from task requirements. However, existing benchmarks predominantly rely on predefined specifications, which limits scalability and hinders truly autonomous evolution. While recent studies attempt to dynamically generate tools, they primarily emphasize downstream performance, resulting in a “black-box” evaluation that makes it difficult to attribute failures to specific causes. To address this, we propose Tool-Genesis, a […]

Ver mais

Hi everyone, I’m trying to consolidate some of my older and newer research work and post it on arXiv. However, I realized that I need an endorsement for the category I’m submitting to. https://arxiv.org/auth/endorse?x=SLMGCF Since I’ve been working independently, I’m not sure how to obtain one. If anyone here is able to help with an endorsement or can point me in the right direction, I’d really appreciate it. Thanks! 🙏 submitted by /u/CodingIsArt [link] [comments]

Ver mais

How Small Can Image Classifiers Get? My Experiments with Ultra-Lightweight Models Most image classification work today is about pushing accuracy higher and higher, usually by throwing more parameters at the problem. This project goes in the opposite direction: how small can the model get while still being useful? This post covers two tasks from TinyVision (v3): a cat vs dog classifier built around a handcrafted feature pipeline, and a CIFAR-10 classifier that ditches the filter bank entirely and […]

Ver mais

arXiv:2602.18448v1 Announce Type: new Abstract: Administrative phone tasks drain roughly 1 trillion USD annually from U.S. healthcare, with over 500 million insurance-benefit verification calls manually handled in 2024. We introduce INSURE-Dial, to our knowledge the first public benchmark for developing and assessing compliance-aware voice agents for phase-aware call auditing with span-based compliance verification. The corpus includes 50 de-identified, AI-initiated calls with live insurance representatives (mean 71 turns/call) and 1,000 synthetically generated calls that mirror the same workflow. All […]

Ver mais

Multi-agent LLM systems enable advanced reasoning and tool use via role specialization, yet reliable reinforcement learning (RL) post-training for such systems remains difficult. In this work, we theoretically pinpoint a key reason for training instability when extending group-based RL to multi-agent LLM systems. We show that under GRPO-style optimization, a global normalization baseline may deviate from diverse agents’ reward distributions, which ultimately leads to gradient-norm instability. Based on this finding, we propose Dr. MAS, a simple and stable […]

Ver mais

How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The Long Now of the Web: Inside the Internet Archive’s Fight Against Forgetting By @zbruceli [ 18 Min read ] A deep dive into the Internet Archive’s custom tech stack. Read More. CodeRabbit vs Code Reviews in Kilo: Which One Is Best For You […]

Ver mais