Search: “agents”

arXiv:2606.01567v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on reusable skills i.e. documents describing task-specific procedures. However, this introduces a

arXiv:2606.02357v1 Announce Type: cross Abstract: Tool-augmented multimodal agents show strong benchmark gains, often taken as evidence that agents have learned to use tools. We argue that this interp

arXiv:2512.16167v3 Announce Type: replace-cross Abstract: Decentralized LLM-based multi-agent service economies face three vulnerabilities that undermine traditional trust mechanisms: reduced cost of

Introducing Devin Desktop: the next generation of Windsurf Manage fleets of local and cloud agents from one surface Support for any ACP-compatible agent With a full IDE for when you need to jump into

Microsoft just announced 'Project Solara,' a new OS designed for gadgets that run AI agents, at Build 2026. The company is calling it 'a new platform built from the ground up to power agent-driven exp

arXiv:2606.01993v1 Announce Type: cross Abstract: Abundant procedural knowledge on the Web holds great potential for helping agents solve long-horizon tasks. However, such knowledge is often multimoda

arXiv:2606.00341v1 Announce Type: cross Abstract: As AI agents are increasingly deployed in real personal and corporate settings (email accounts, development workflows, company databases, etc.), safet

arXiv:2606.01613v1 Announce Type: cross Abstract: This paper presents an agentic retrieval-augmented generation (RAG) framework for domain-specific technical reasoning support, instantiated over a cur

arXiv:2606.00953v1 Announce Type: new Abstract: Multi-agent Large Language Model (LLM) systems offer a way to decompose complex tasks, such as coding, through parallelization and context isolation. Ho

Enterprise AI adoption at scale requires moving beyond large language models to implement agent logic systems that can handle complex reasoning, planning, and decision-making autonomously. Agent-based

Connecting agents directly to Snowflake, Slack, or BigQuery via MCP/CLIs is a multi-token disaster. They default to brute-force exploration, firing 20-30 tool calls just to rediscover context on every

arXiv:2605.11946v2 Announce Type: replace Abstract: Large Language Model agents are increasingly augmented with agent skills. Current evaluation methods for skills remain limited. Most deployed benchm

arXiv:2605.31377v1 Announce Type: cross Abstract: Agentic Retrieval-Augmented Generation improves retrieval by integrating planning, tool use, and iterative reasoning, but existing agentic RAG methods

if you build any agent on activegraph, the trace is automatic and first-class, not bolted on a parallel experiment building a coding agent on top of @activegraphai. you can see everything flattened do

arXiv:2605.30848v1 Announce Type: cross Abstract: Agentic LLMs with web search change the threat model for text anonymization: weak contextual cues can become cross-referenceable evidence for re-ident

The Perplexity Agent API documentation includes a 'Search as Code' feature accessible through the sandbox tools section, enabling developers to integrate search functionality programmatically within a

🧑‍⚖️Evaluating Deep Agents with LangSmith on AWS Great deep dive blog with our friends at AWS on evaluating DeepAgents with LangSmith Covers datapoint and evaluator design for longer horizon agents ht

Learn more about the latest from @james_y_zou and our Frontier Agents Research team! To evaluate frontier AI agents, we need more complex tasks. But such tasks are also more prone to have design mista

Step 3.7 Flash is now free for 30 days via Nous Portal It is a new MoE vision-language model focused on agent efficiency, coding, search, and multimodal workflows — and Hermes Agent users have been lo

arXiv:2605.30144v1 Announce Type: new Abstract: Despite the rapid deployment of LLMs into classrooms, validating educational AI remains uniquely intractable: interventions act on developing learners w

arXiv:2605.29927v1 Announce Type: cross Abstract: Despite recent advances, LLM-based web agents still struggle with limited exploration, omission of critical steps, and sensitivity to task constraints

arXiv:2605.29129v1 Announce Type: new Abstract: Agentic AI systems are increasingly being explored as production infrastructure: they reason over multiple steps, call tools, act through workflows, and

arXiv:2605.29960v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly leverage long term memory to support persistent and autonomous task execution. However, this capability

make something agents want studying ActiveGraph by @yoheinakajima and apart from the concept the implementation itself is brilliant on the site it shares a prompt that will make my agent study docs, i

arXiv:2605.29253v1 Announce Type: new Abstract: Task success can hide process anomalies in real-world agent executions. An agent may pass the final task oracle while still accumulating unresolved ambi

arXiv:2605.29861v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced autonomous agents from deep search, which retrieves concise factual answers, to deep research, which synthe

a hot (cold at this point?) take that lead us to build this: every agent in the future will need a sandbox to connect to writing/executing code is not just for coding agents! is useful for all sorts o

arXiv:2605.27898v1 Announce Type: new Abstract: As LLMs are increasingly deployed as agents, reliable assessment of their agentic capabilities has become essential. However, reported benchmark scores

arXiv:2605.22166v2 Announce Type: replace Abstract: LLM agents are shaped not only by their language models, but also by the runtime harness that mediates observation, tool use, action execution, feed

arXiv:2605.28108v1 Announce Type: new Abstract: A long-lived LLM agent, such as OpenClaw, earns its value by acting on a user's preferences and constraints across sessions, not just the current reques

arXiv:2605.27820v1 Announce Type: new Abstract: As AI agents increasingly operate in open, real-world environments, they require a deep synergy of multimodal perception, tool invocation with multi-hop

arXiv:2605.27384v1 Announce Type: cross Abstract: This position paper reflects empirical data collected during my PhD from a large-scale within-subjects study (N = 90). The study compared a highly hum

arXiv:2605.28534v1 Announce Type: new Abstract: Despite the rapid progress of multimodal large language models in building Graphical User Interface (GUI) agents, their real-world task completion is fu

Endava, a software services company, leverages OpenAI's Codex to transform its organizational operations into an agentic model where AI agents autonomously handle tasks and decision-making. The approa

Is grep 𝘳𝘦𝘢𝘭𝘭𝘺 all your AI agent needs for search? For a small codebase or a docs folder, the answer might be yes, but in most enterprise environments, agents face millions of PDFs, spreadsheets, and

okay i think this is a much better visualization of what i mean by 'log-centric agent architecture' babyagi has ~200 citations, but 0 papers... i just published my first paper on arXiv 😆 'The Log is t

Orchid Security Inc. today extended its Identity Control Plane with a set of capabilities aimed at governing artificial intelligence agents, saying existing identity and access management models canno

arXiv:2605.26642v1 Announce Type: new Abstract: Collaborative perception improves 3D object detection by enabling agents to share complementary observations, but most existing methods assume fixed or

arXiv:2602.08586v3 Announce Type: replace Abstract: Multi-agent LLM systems consistently outperform single-agent baselines, yet practitioners still cannot predict which design works for a new task or

arXiv:2605.26952v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has proven effective for training LLM-based agents with external tool-use capabilities. However, we identify that ag

arXiv:2509.04310v4 Announce Type: replace Abstract: Recent research on Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs) has demonstrated that agents can engage in extit{complex}, extit

i first wrote down the agent labs thesis last year https://x.com/swyx/status/1990886806250782876?s=46 New @latentspacepod Essay: why Agent Labs are clearly emerging in 2025 as a complement to Model La

It's crazy that this is even possible today. It inspired me to build my own self-improving coding agent with simple read, write, bash,... I already used the coding agent to build an entire production-

arXiv:2605.27042v1 Announce Type: cross Abstract: As AI systems gain increasing autonomy and execution capability, the number of discovered security vulnerabilities continues to rise. However, many of

arXiv:2605.27320v1 Announce Type: new Abstract: Agentic AI systems combine probabilistic reasoning with delegated action through tools, context, memory, orchestration, and external workflow integratio

oh yeah first* automations - instead of dumb crons kicking of agents, devin has made them smart. try it - it is the first non annoying proactive agent impl ive seen https://x.com/russelljkaplan/status