Search: “tools”

When scaling up agentic reinforcement learning (RL) and evaluation across massive parallel rollouts, frontier AI labs inevitably hit a bottleneck: Expensive GPU clusters sit idle, waiting minutes for

arXiv:2602.14907v3 Announce Type: replace-cross Abstract: Adjoint-based shape optimization of ship hulls is a powerful tool for addressing high-dimensional design problems in naval architecture, parti

arXiv:2609.33323v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, v

An agentic security strategy must account for software that can act on legitimate instructions in unexpected ways. Agents can use credentials, call tools and choose their own routes toward a goal, exp

arXiv:2609.35247v1 Announce Type: new Abstract: When a VLM answers a visual query, current interpretability tools rely on text rationales, which use a mismatched modality, or on internal read-outs, wh

Harness distillation can train general scaffolding into a model. The harness that remains is the part tied to your tools, data, users, and environment. The post Are agent harnesses dying? What harness

arXiv:2609.33802v1 Announce Type: cross Abstract: Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably succe

arXiv:2609.32961v1 Announce Type: new Abstract: As LLM agents tackle longer tasks, they increasingly compress growing histories of reasoning, actions, and tool outputs. Compression can reduce token us

Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platform on AWS that uses

arXiv:2609.33549v1 Announce Type: cross Abstract: Automatic relevance determination (ARD), the default tool for variable selection in Gaussian-process (GP) regression, ranks inputs by inverse lengthsc

arXiv:2609.32255v1 Announce Type: cross Abstract: Tool-using LLM agents must decide not only whether additional information is needed, but also which source can resolve the uncertainty. Existing proac

arXiv:2609.31653v1 Announce Type: cross Abstract: Sentiment analysis is a common tool for converting unstructured text into quantitative signals in finance and risk management. Yet most applications r

arXiv:2602.08847v2 Announce Type: replace Abstract: Multi-agent LLM systems enable advanced reasoning and tool use via role specialization, yet reliable reinforcement learning (RL) post-training for s

EliseAI, a startup that develops artificial intelligence tools for real-estate companies and healthcare providers, has raised 350 million in funding. Andreessen Horowitz and Bessemer jointly led the r

arXiv:2609.32190v1 Announce Type: new Abstract: DNA methylation (DNAM) profiling has emerged as a powerful diagnostic tool for classifying brain and solid tumors. However, existing computational model

arXiv:2602.04553v2 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving differential equations, yet their application to nuclear scatteri

arXiv:2609.32555v1 Announce Type: new Abstract: Dynamic contrast enhanced breast MRI (DCE-MRI) is a powerful clinical tool for breast cancer detection, providing high resolution anatomical detail toge

arXiv:2510.04979v2 Announce Type: replace Abstract: Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are fundamental analytical tools for evaluating classification models, prov

arXiv:2609.35738v1 Announce Type: cross Abstract: A language-model agent is jointly defined by its model and its harness, the executable program that organizes model calls, tool use, and information f

arXiv:2609.32213v1 Announce Type: new Abstract: Agent performance depends on both the underlying model and the harness that manages its tool use and execution. Selecting a suitable pair requires accou

Every major security shift ultimately comes down to one question: Who or what is allowed to do this? For most of the past two decades, the answer was a person with a username and password. In the arti

IQuest-Q1 is a Mixture-of-Experts (MoE) model developed by IQuest for agentic coding, reasoning, and multi-step tool use. It comprises approximately 320B total parameters, with an estimated 15B parame

arXiv:2609.34931v1 Announce Type: cross Abstract: Machine learning has made strong progress on music tasks, both as assistive tools and as creative partners. However, most systems train on multitrack

arXiv:2609.34276v1 Announce Type: new Abstract: Frontier models can now perform well on individual embodied navigation tasks through multi-round multimodal reasoning with simple tools. Across successi

arXiv:2609.32302v1 Announce Type: new Abstract: Prompt engineering has become an indispensable tool for using large language models (LLMs), turning LLMs into task-specific experts without changing the

arXiv:2609.32732v1 Announce Type: cross Abstract: Human mobility generation aims to synthesize realistic point-of-interest (POI) visitation trajectories and has become an important tool for travel beh

arXiv:2609.34179v1 Announce Type: cross Abstract: Retrieval-augmented generation systems are extensively instrumented with metrics, benchmarks, traces, and automated judges, but these tools do not dec

arXiv:2609.35576v1 Announce Type: cross Abstract: Large language models are increasingly deployed as stateful assistants that retain information across interactions and use tools to read, modify, and

arXiv:2609.33774v1 Announce Type: cross Abstract: Watermarking is a promising tool for establishing the provenance of AI-generated speech. While many neural audio watermarking methods rely on a separa

arXiv:2609.34682v1 Announce Type: new Abstract: Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past ex

arXiv:2609.35020v1 Announce Type: new Abstract: Vision Sparse Autoencoders (SAEs) have become a popular tool in Mechanistic Interpretability due to their presumed ability to disentangle complex featur

arXiv:2609.30859v1 Announce Type: cross Abstract: Contingency analysis using the AC power flow (AC-PF) model is a critical tool for accurate grid security assessment, but its computational burden incr

arXiv:2609.31418v1 Announce Type: new Abstract: A photorealistic 3D view tells a teleoperator where a robot is, but not what the scene contains, how well each object has been observed, or how to turn

arXiv:2609.31587v1 Announce Type: cross Abstract: We investigate whether natural-language documentation helps coding agents resolve software issues, and we build the tools to construct and evaluate it

arXiv:2609.31469v1 Announce Type: cross Abstract: Shapley values, a solution concept from cooperative game theory, have recently become a standard tool for feature credit allocation in machine learnin

arXiv:2604.15186v2 Announce Type: replace-cross Abstract: Agentic workflows carry out complex tasks by orchestrating multiple large language models (LLMs) and tools. Serving them at a target throughpu

Fizgig 6.5 is out with Qwen Image 2.1 LoRA and LoKR training, turbo previews, and all the workbench tools. Supports 10GB VRAM+. I also trained a new training adapter as the existing one felt like it l

Good day data nerds! I am trying to get more into running models, learning about agentic workflows, and creating my own tools. But as you do (right?) I had to fine tune my current setup. With the way

Help: Project l'm building a shelf audit tool. A photo goes through YOLO, which crops each product, and then I embed the crop and search a small gallery of reference photos to get the SKU. New product

Tool: Kākāpō Party I presented a closing keynote for the WeAreDevelopers World Congress North America yesterday. As a STAR moment I decided to weave in references to the record breaking kākāpō breedin

Hi everyone, I built an educational tool that shows what happens inside a small MLP while it trains, and I'd like some feedback from people who teach ML. Everything is plain NumPy, no autograd: manual

Which one is better for difficult tasks like web scrapping, coding, using tools? Looking for any benchmarks because i couldn't actually find one after quite some digging submitted by /u/Loose_Doubt367

arXiv:2609.29154v1 Announce Type: new Abstract: Large language model agents increasingly rely on natural-language skills to solve complex tool-use tasks. However, such tasks often admit multiple valid

arXiv:2609.28557v1 Announce Type: new Abstract: DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems

arXiv:2609.30058v1 Announce Type: cross Abstract: AI-assisted job-search tools have become increasingly popular by making it easier to find and apply to jobs. But by making it easier for applicants to

Describe the interface you need in plain English, then let the agent build a live surface you can both use and update—so you spend less time adapting to tools and more time getting work done. The post