Search: “agents”

arXiv:2604.13954v1 Announce Type: new Abstract: Existing agent-safety evaluation has focused mainly on externally induced risks. Yet agents may still enter unsafe trajectories under benign conditions.

LiteParse should be the default document parser you use with any AI agent (Claude Code, Claude Cowork, OpenClaw, Codex, and more) The core is extremely fast text and accurate parsing from any document

arXiv:2604.12762v1 Announce Type: cross Abstract: We introduce ARGOS, the first benchmark and framework that reformulates multi-camera person search as an interactive reasoning problem requiring an ag

I'm going all in on Hermes (@NousResearch, @Teknium1) as my entire agent and coding stack. Six profiles. One shared self-hosted memory store. Zero hosted-coder dependencies. The fleet: - pmax-mousa —

An open-source agent self-reflection harness built on top of Ollama, shared in the r/ollama community, that enables locally run LLMs to evaluate and iteratively refine their own outputs. The project p

arXiv:2604.12282v1 Announce Type: new Abstract: Spreadsheets are central to real-world applications such as enterprise reporting, auditing, and scientific data management. Despite their ubiquity, exis

arXiv:2604.09621v1 Announce Type: new Abstract: We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agen

arXiv:2604.09813v1 Announce Type: new Abstract: Existing synthetic tool-use corpora are primarily designed for offline supervised fine-tuning, yet reinforcement learning (RL) requires executable envir

arXiv:2604.01236v2 Announce Type: replace-cross Abstract: Traditional network architectures suffer from severe protocol ossification and structural fragility due to their reliance on static, human-def

arXiv:2604.09666v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) and its graph-based extensions (GraphRAG) are effective paradigms for improving large language model (LLM) reason

arXiv:2604.09568v1 Announce Type: cross Abstract: High-fidelity diagram creation requires the complex orchestration of semantic topology, visual styling, and spatial layout, posing a significant chall

arXiv:2604.10989v1 Announce Type: new Abstract: Emergency situations in scheduling systems often trigger local functional failures that undermine system stability and even cause system collapse. Exist

Most AI assistants wait for you to ask. But a truly useful agent should notice you need help before you say anything. New research takes a serious shot at building proactive agents that work in real t

arXiv:2604.10261v1 Announce Type: new Abstract: Existing tool-use benchmarks for LLM agents are overwhelmingly linear: our analysis of six benchmarks shows 55 to 100% of instances are simple chains of

arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim

We've been developing a multi-agent system that builds and maintains complex software autonomously. Recently, we partnered with NVIDIA to apply it to optimizing CUDA kernels. In 3 weeks, it delivered

arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com

a big part of agent harnesses is how they interact with context memory is just context its therefor impossible to separate harness from memory - as @sarahwooders says, 'memory isn't a plugin (it's a h

arXiv:2511.08605v3 Announce Type: replace Abstract: Bangladesh's low-income population faces major barriers to affordable legal advice due to complex legal language, procedural opacity, and high costs

arXiv:2604.07765v1 Announce Type: new Abstract: Earth Observation (EO) systems are essentially designed to support domain experts who often express their requirements through vague natural language ra

GLM-5.1 is Z.ai's post-training upgrade to GLM-5, now available on Together AI, delivering a 28% coding performance improvement through a refined reinforcement learning pipeline while retaining the...

How can you improve your agentic search pipeline? I just wrote a blog post with @tech_optimist from @lancedb to answer exactly that. TLDR: - Parse files and take page-level screenshots with LiteParse,

arXiv:2602.16653v4 Announce Type: replace Abstract: Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and

It’s no secret that Grok @Bot is my favorite 24/7 AI agent right now. I’m partnering with @SpaceXSI to give out codes for one month FREE of the Super tier ($100) of their new X Subscription. It combin

arXiv:2610.21283v1 Announce Type: new Abstract: Code world models represent world dynamics through explicit state and executable rules. We investigate how to coordinate object representations, behavio

arXiv:2610.21394v1 Announce Type: cross Abstract: Matoi separates reusable consequence evidence from current execution authority and durable occurrence history. Its finite query-aware contract covers

arXiv:2610.22269v1 Announce Type: new Abstract: The O-RAN ALLIANCE introduces architectural flexibility through disaggregation and AI-driven control. While the RAN Intelligent Controller (RIC) enables

arXiv:2610.18760v1 Announce Type: new Abstract: Test-time scaling for large language models (LLMs) can involve generating multiple candidate solutions for selection or revising an earlier attempt. To

arXiv:2610.18880v1 Announce Type: new Abstract: High-throughput perturbation screens increasingly use machine-learning models to predict the effects of gene combinations that were never measured. A di

arXiv:2610.17840v1 Announce Type: new Abstract: Multi-agent deliberation can improve recognition by criticizing and revising candidate answers, but fixed controls cannot respond to changes in disagree

arXiv:2610.17763v1 Announce Type: new Abstract: Long-term memory supports agents across sessions. Repeated retrieval and write-back can let one historical claim occupy multiple retrieval positions and

arXiv:2603.06977v3 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, trai

Nvidia Corp. today announced the launch of customizable Nemotron 3.5 Super LV large language models for always-on artificial intelligence agents and edge-focused 3.5 Bolt for local systems. The compan

arXiv:2606.20235v2 Announce Type: replace-cross Abstract: Academic paper search is a core step in scientific research, and LLM-based search agents are emerging as a promising paradigm for iterative, i

arXiv:2610.18813v1 Announce Type: new Abstract: Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model wei

arXiv:2606.14715v2 Announce Type: replace-cross Abstract: LLM agents are increasingly used to simulate real-world interactions, but it remains unclear whether simulated behaviors preserve the content

arXiv:2610.14574v1 Announce Type: cross Abstract: In-context learning (ICL) allows large language models to use demonstrations without updating their parameters. For interactive agents, demonstrations

arXiv:2610.16867v1 Announce Type: new Abstract: Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achiev

arXiv:2506.02841v5 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms

arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu

arXiv:2610.14968v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate functionally correct code while introducing exploitable security weaknesses, particularly when developers sp

arXiv:2603.01714v2 Announce Type: replace Abstract: Training tool-use agents typically relies on outcome-based filtering: Supervised Fine-Tuning (SFT) on successful trajectories and Reinforcement Lear

arXiv:2610.13947v2 Announce Type: replace Abstract: In this paper, we study physically grounded articulated 3D asset generation---moving the goal from reproducing how objects look to capturing how the

arXiv:2610.15038v1 Announce Type: new Abstract: Real-world Vision-Language Navigation (VLN) requires agents to act under partial observability, where map structure, semantic cues, and target locations

Companies in France are deploying agentic computing across industries spanning space, financial services, the public sector and scientific research, demonstrating how the country’s ecosystem has moved

Niel Pal hosted the Agent Economy Gala last week—a rare Black‑Tie event held in San Francisco that drew approximately 300 builders and investors. The evening featured participants from the llama_index