Search: “agents”

MODEL + GGUF : https://huggingface.co/InternScience/models?search=a1-4b Technical Report Benchmark Qwen3.5-4B Agents-A1-4B Qwen3.5 Qwen3.6 Nex-N2-mini Agents-A1 🧠 Dense Models (~4B) 🔀 MoE Models (35B-

arXiv:2607.12058v1 Announce Type: cross Abstract: Given a vulnerability-fixing commit, trigger localization asks which specific statement turns the vulnerable program state into a concrete unsafe oper

arXiv:2607.12050v1 Announce Type: new Abstract: Multi-robot teams operating in confined or cluttered environments must adapt both their formation geometry and group topology to navigate through comple

arXiv:2607.12650v1 Announce Type: cross Abstract: Tool access alone does not make LLM empirical reasoning governable: accepted outputs need not descend from attested evidence, and accepted deductions

arXiv:2607.12042v1 Announce Type: new Abstract: Visual generation is increasingly ubiquitous in diverse domains, from text-to-image/video synthesis to multimodal interactive creation. Yet prevailing m

Autonomous coding agents such as Codex (GPT‑5.5) can fully automate reinforcement‑learning research workflows by provisioning GPU‑hosted environments, orchestrating experiments, and iteratively optimi

In this post, we describe how Bluesight used two AWS engagements and Amazon Bedrock AgentCore to evolve from a single-product AI prototype to Prism, a unified agentic AI solution spanning six healthca

arXiv:2306.02704v2 Announce Type: replace-cross Abstract: We introduce Calibrated Stackelberg Games (CSGs), a generalization of the standard Stackelberg Games (SGs) framework. In CSGs, a principal rep

Agentic marketing leverages AI agents to automate marketing tasks, and this approach requires a robust data foundation as its core component. Databricks discusses how organizations need unified data p

arXiv:2607.08010v1 Announce Type: new Abstract: Production LLM agents often waste latency and reliability by regenerating code for the same procedural steps on every request. We replace this inference

A demonstration of an AI agent with iPhone integration that autonomously ordered a donut, showcasing early progress in agentic AI capabilities. The demo was presented publicly by AGI Inc and Div Garg,

Soak testing for AI agents involves running agents continuously over extended periods to identify performance degradation, resource leaks, stability issues, and edge cases that may not appear during s

arXiv:2607.07612v1 Announce Type: cross Abstract: Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks. Widely charact

arXiv:2607.05775v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly evaluated on their ability to use tools, plan multi-step tasks, coordinate with other agents, and ope

arXiv:2607.03220v1 Announce Type: cross Abstract: Recent tools such as OpenClaw have extended the capabilities of LLM-based agents from simple dialog-based systems to fully autonomous agents. These sy

arXiv:2607.03821v1 Announce Type: cross Abstract: Personal AI agents that run on the user's local machine, such as OpenClaw, automate daily tasks including web search, email, and file management. Thei

This post discusses the current state of standardization for agent execution trace formats, questioning whether ATIF (Agent Trace Interchange Format) or alternative formats have achieved adoption, or

arXiv:2607.05188v1 Announce Type: new Abstract: A coding agent solving a software-engineering task spends dozens of steps reasoning, editing code, and running tests, yet little is known about what the

arXiv:2607.04409v1 Announce Type: new Abstract: Learning and planning in imagination using world models provides an effective paradigm for training agents for decision-making. However, existing approa

arXiv:2607.04528v1 Announce Type: new Abstract: Software-agent benchmarks usually report whether an agent solves a task, but the agent reaches that outcome through a harness that controls what it sees

arXiv:2607.03228v1 Announce Type: new Abstract: LLM-based agents offer new opportunities for automating business process execution beyond the limits of rule-based systems. However, general-purpose LLM

arXiv:2607.03695v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in interacting populations, raising the question of what such populations come to believe co

We're hosting the LA Agentic AI Meetup this Thursday, July 9, 5 to 7pm at Gulp in Playa Vista. Come talk to engineers, founders, and builders working across RAG, agentic workflows, and the broader AI

This post discusses using deep agents and OpenKeyFlow (OKF) for a wiki project built with LangGraph, a framework for constructing agent-based applications. The developer is leveraging LangGraph's capa

Can coding-agents replicate scientific ML papers? We know this is possible because we can already do this @dair_ai. Still a great read. So they try to replicate an ML paper from its materials alone. T

arXiv:2607.01584v1 Announce Type: new Abstract: Large language models have recently been explored for scientific hypothesis generation, but most prior work relies on unstructured literature and free-f

arXiv:2607.01236v1 Announce Type: cross Abstract: As LLM agents gain increasing access to powerful tools, ensuring that their actions are aligned with the user's intent becomes critical. When an agent

arXiv:2607.01507v1 Announce Type: new Abstract: Empirical research rarely admits a unique analysis. Different analytical choices can lead to different conclusions from the same data, yet these hidden

arXiv:2607.02186v1 Announce Type: new Abstract: Software development is a complex task that demands cooperation among agents with diverse roles. Large language models (LLMs) have enabled autonomous mu

This post discusses using WorkPods agent memory systems organized as wikis, likely exploring how LLM agents can maintain and access persistent knowledge repositories in wiki format for improved contex

arXiv:2607.01047v1 Announce Type: new Abstract: Complexity and interpretability rarely coincide: systems rich enough for complex behaviours to emerge are usually too opaque to question, while transpar

Agent evals are repeatable tests that score whether AI agents completed a task correctly. Learn how to design rubrics, test suites, and trace-based evals that catch failures and prevent reward hacking

LLM Wikis are being slept on. I argue that creating knowledge bases with LLMs or coding agents is one of the most valuable applications of AI today. It's about being intentional in building and scalin

Special episode with @bentannyhill on the Max Agency podcast. A month ago, his team shipped LangSmith Engine, our agent that hunts through your agent's failures, prioritizes issues, and drafts the fix

arXiv:2606.31564v1 Announce Type: new Abstract: The increasing complexity of agentic tasks has led to rapidly growing trajectory lengths, which poses significant challenges for large language model (L

arXiv:2606.31831v1 Announce Type: new Abstract: High-throughput plant phenotyping now generates image derived datasets far faster than scientists can analyze them. At Oak Ridge National Laboratory's A

arXiv:2601.04126v3 Announce Type: replace-cross Abstract: GUI agents that interact with graphical interfaces on behalf of users represent a promising direction for practical AI assistants. However, tr

arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents

The article covers the Supabase plugin for OpenCode, an AI coding agent, which bundles the Supabase MCP server and agent skills for direct database and project interaction . The plugin ships official

arXiv:2606.29194v1 Announce Type: new Abstract: Automated alpha mining holds the scoring function fixed and varies the search algorithm over it. A search that converges against a fixed scorer overfits

arXiv:2606.30246v1 Announce Type: new Abstract: Existing autonomous research agents can support parts of the research process, but most systems still treat research as either an isolated assistant tas

arXiv:2606.29705v1 Announce Type: new Abstract: Data, as the fundamental substrate of modern intelligence, has greatly driven the development of current foundation models. Naturally, researchers aim t

arXiv:2606.29648v1 Announce Type: cross Abstract: Different retrievers, including lexical, semantic, and multimodal approaches, provide highly complementary strengths for multimodal document understan

arXiv:2606.27944v1 Announce Type: cross Abstract: Phone-use Agents can execute complex tasks end to end across real mobile applications. By operating a real device on the user's behalf, they reach far

arXiv:2606.29778v1 Announce Type: cross Abstract: Long-term conversational agents need to remember and query cross-session, multi-typed information with complex correlations. Existing agent memory sys

arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat