Search: “tools”

arXiv:2610.18067v1 Announce Type: cross Abstract: Scaling interactive environments is important for training long-horizon agents through reinforcement learning. These environments often require furthe

arXiv:2610.14861v1 Announce Type: new Abstract: Time-series forecasting plays a vital role in a wide range of real-world applications. Recent approaches have achieved strong performance by modeling te

Epic Games plans to use AI to generate code and art for an unannounced Disney game, which is now delayed from its original March release window, according to a report from Bloomberg. The project's dev

I started Flama in 2018 to take a trained model to a production API with as little ceremony as possible. With 2.0 LLMs became first-class alongside classic models, and together with Miguel Durán-Olive

If an agent saves an engineer 2 hours to implement a feature but collectively costs the team 3 hours in alignment and review, the ROI is negative. Isolated chats are suboptimal in team environments be

https://preview.redd.it/p6i9qifyy8vh1.png?width=2069&format=png&auto=webp&s=2b1e3c7c4fc95f12f0f7d417a4d21410aebfbd35 The 3090 Founders edition has a reputation for hot VRAM. Since LLM token generation

IBM Research has presented a new approach that scales AI‑driven chip design by employing open “agent factories,” lowering inference cost by 11.5 × compared to fully proprietary setups. The method enab

Reuters: Sources: US banking regulators are questioning banks about their deployment of agentic AI, use of Chinese-developed AI models, and autonomous system safeguards — Banking regulators are steppi

Enterprise management software company Workday Inc. today announced that it wants to turn its existing knowledge of people, money and business rules into an operational foundation for agentic artifici

A decade ago, Google released Site Reliability Engineering: How Google Runs Production Systems with O'Reilly Media. What began as a collection of our practices for managing large-scale infrastructure

arXiv:2510.10998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly under scrutiny for perpetuating identity-based discrimination in high-stakes domains such as hir

arXiv:2610.12500v1 Announce Type: cross Abstract: Alzheimer's disease (AD) remains a major public health challenge, and early identification is crucial for timely intervention and care planning. Recen

arXiv:2610.13273v1 Announce Type: cross Abstract: API specifications serve as critical documentation for modern software development, directly impacting integration efficiency and client code generati

arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has

arXiv:2610.13627v1 Announce Type: new Abstract: Evaluating large language models (LLMs) on AMLworld's smallest test splits is costly because each of over a million targets requires a separate graph pr

arXiv:2602.01709v3 Announce Type: replace Abstract: Current test-time scaling (TTS) techniques enhance large language model (LLM) performance by allocating additional computation at inference time, ye

arXiv:2610.13862v1 Announce Type: new Abstract: Deploying language-model agents onboard mobile robots requires task reasoning and responsive execution within limited compute and memory. We propose BT-

arXiv:2610.13025v1 Announce Type: new Abstract: Self-evolving agents are increasingly used to improve language model systems without human intervention through either weight updates or harness improve

arXiv:2610.12793v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies fail on memory tasks, behaviour that depends on events observed long before the current frame, because

arXiv:2610.13494v1 Announce Type: new Abstract: Existing LLM-based agent approaches for long-horizon machine learning engineering (MLE) often use context engineering, implemented through custom harnes

I've been investigating some serious ChatGPT reliability issues over the past several days, and my latest tests revealed something particularly interesting: Both GPT-5.6 and GPT-6 showed problems unde

Agents are only as capable as the context they can reach. An agent with reliable access to the right information makes decisions grounded in fact; one without it guesses. And the work agents produce i

arXiv:2610.12518v1 Announce Type: cross Abstract: This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a

arXiv:2610.13829v1 Announce Type: cross Abstract: A central challenge in embodied recursive self-improvement is enabling agents to convert interaction history into capabilities that persist beyond one

arXiv:2610.12963v1 Announce Type: cross Abstract: Video editing models achieve strong performance in modifying appearance, backgrounds, styles, and motions, empowered by large-scale training data. Bey

Nice paper on optimizing agents and their graders together. The key finding is that you want to update your LLM grader alongside the agent instead of keeping it fixed, because the agent's failure mode

arXiv:2610.13790v1 Announce Type: cross Abstract: How well can vision-language models (VLMs) reason about what is missing from an image? We study this question with OccludeBench, a manually curated be

Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo

EXL3-QLoRA I've built this over the last few months and I think it's stable enough to share now. A fork of ExLlamaV3, this is a native ExLlamaV3 training implementation with plain PyTorch, without tra

arXiv:2610.13152v1 Announce Type: new Abstract: Open coding agents are commonly trained through supervised fine-tuning on interaction trajectories whose final patches pass the benchmark test suite. Ho

arXiv:2610.13438v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and to

arXiv:2610.13527v1 Announce Type: cross Abstract: Multimodal language models (MLLMs) exhibit promising spatial reasoning capabilities, yet the internal mechanisms supporting them remain poorly underst

arXiv:2610.13207v1 Announce Type: new Abstract: Fake news detection under low resource conditions is challenged by the scarcity of labeled data and the difficulty of capturing subtle deceptive pattern

arXiv:2610.12975v1 Announce Type: new Abstract: We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents agains

arXiv:2610.13835v1 Announce Type: new Abstract: An ideal (language) model must continually update its knowledge. Existing work largely focuses on making these updates efficient after training. We inve

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

arXiv:2610.13461v1 Announce Type: new Abstract: AI systems are making rapid progress in mathematics, but this progress is hard to measure. Benchmarks of solved problems saturate, and in benchmarks of

Brock E.W. Turner / Axios: Suki, an AI ambient scribe for healthcare providers, raised a 90M Series E led by Healthier Capital; a source says it projects 60M-80M in revenue this year — Suki, a health

arXiv:2610.13356v1 Announce Type: new Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success c

arXiv:2610.12828v1 Announce Type: new Abstract: Outcome-supervised group-relative policy optimization (GRPO) assigns the same advantage to every token in an LLM agent trajectory, leaving useful and un

arXiv:2412.06534v5 Announce Type: replace-cross Abstract: Understanding the internal mechanisms of deep neural networks remains a central challenge in machine learning. In computer vision, one promisi

arXiv:2610.13098v1 Announce Type: new Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous su

arXiv:2610.12832v1 Announce Type: new Abstract: Pretrained vision-language models (VLMs) already exhibit strong visual, spatial and reasoning capabilities relevant to robotic manipulation. The key cha

At NetApp INSIGHT 2026, Vultr highlighted the emerging “beyond hyperscale” era of enterprise infrastructure, emphasizing that agentic AI and modernized applications require more than compute and stora

arXiv:2603.17917v2 Announce Type: replace-cross Abstract: Large language models (LLMs) contain billions of parameters, but many exact weight values are not essential. We apply scalar K-means clusterin

Financial institutions are adopting artificial intelligence faster than many compliance teams can establish the controls needed to oversee it. That gap is raising new questions about AI-powered compli