Search: “agents”

arXiv:2604.20486v1 Announce Type: new Abstract: Training multimodal agents via reinforcement learning for knowledge-intensive visual reasoning is fundamentally hindered by the extreme sparsity of outc

zero shot Kimi K2.6, go try it out its a good model sir! this is @Kimi_Moonshot running on @togethercompute, @opencode harness prompt below👇 Media Introducing Kimi K2.6 from @Kimi_Moonshot, a multimod

arXiv:2604.19533v1 Announce Type: cross Abstract: We introduce the Cyber Defense Benchmark, a benchmark for measuring how well large language model (LLM) agents perform the core SOC analyst task of th

Meta employees' activity at work is now being used to train the company's AI agents. As reported by Reuters, Meta is installing a tool it calls Model Capability Initiative (MCI) on US-based employees'

arXiv:2601.04237v2 Announce Type: replace Abstract: We demonstrate SAGE-32B, a 32 billion parameter language model that focuses on agentic reasoning and long range planning tasks. Unlike chat models t

Artificial intelligence and machine learning have been a central focus for Boomi LP over much of its 26 years as a data activation company. The organization began storing anonymized metadata from cust

arXiv:2411.06812v2 Announce Type: replace-cross Abstract: This paper introduces the concept of ``generative midtended cognition'', exploring the integration of generative AI with human cognition. The

Kimi is the current open-source SOTA on Artificial Analysis Moonshot’s Kimi K2.6 is the new leading open weights model. Kimi K2.6 lands at #4 on the Artificial Analysis Intelligence Index (54) behind

Let's talk parsing charts 📊📈. Last week we released ParseBench, the first document OCR benchmark for AI agents. New in ParseBench: ChartDataPointMatch. Most document look at a chart and OCR the captio

arXiv:2511.21064v2 Announce Type: replace-cross Abstract: Open-Vocabulary Object Detection (OVOD) aims to enable detectors to generalize across categories by leveraging semantic information. Although

Global AI ambitions keep colliding with the same wall: cloud infrastructure that can’t keep up with performance demands without compromising where data lives and who controls it. As organizations look

arXiv:2604.15715v1 Announce Type: cross Abstract: The development of general-purpose agents requires a shift from executing simple instructions to completing complex, real-world productivity workflows

arXiv:2604.15373v1 Announce Type: cross Abstract: We propose InfoChess, a symmetric adversarial game that elevates competitive information acquisition to the primary objective. There is no piece captu

arXiv:2604.15671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated significant potential for embodied decision-making; however, their application in complex chemical

arXiv:2604.15505v1 Announce Type: cross Abstract: LLM agents operating under organizational policies must comply with authorization constraints typically specified in natural language. In practice, su

We recently shipped quality-of-life improvements to the Cursor CLI to make working with agents in the terminal more delightful. Use /debug to find root causes and fix tricky bugs that are hard to repr

arXiv:2604.14228v1 Announce Type: cross Abstract: Claude Code is an agentic coding tool that can run shell commands, edit files, and call external services on behalf of the user. This study describes

arXiv:2604.14267v1 Announce Type: new Abstract: Search agents extend Large Language Models (LLMs) beyond static parametric knowledge by enabling access to up-to-date and long-tail information unavaila

LLM agents loop, drift, and get stuck on hard reasoning tasks up to 30% of the time. Current fixes are either too blunt (hard step limits) or too expensive (LLM-as-judge adding 10-15% overhead per ste

arXiv:2604.13630v1 Announce Type: cross Abstract: The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use, context

arXiv:2512.18436v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive capability to understand and develop code. However, their capability to rigorously reason a

Anna Tong / Forbes: AI labs are buying Slack, Jira, and email archives from defunct startups to build “reinforcement learning gyms” and train AI agents in simulated workplaces — Defunct startups are b

arXiv:2604.13072v1 Announce Type: new Abstract: LLM-based agents are increasingly expected to handle real-world assistant tasks, yet existing benchmarks typically evaluate them under isolated sources

⚡ Meet Qwen3.6-35B-A3B：Now Open-Source！🚀🚀 A sparse MoE model, 35B total params, 3B active. Apache 2.0 license. 🔥 Agentic coding on par with models 10x its active size 📷 Strong multimodal perception an

Nous Research🤝fal Congratulations to @NousResearch on the Tool Gateway launch. Developer-first infrastructure is what will define the next phase of agentic applications. Tool Gateway is now live in No

arXiv:2604.14116v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have empowered AI research agents to perform isolated scientific tasks, automating complex, real-world workflows, s

arXiv:2512.14234v2 Announce Type: replace Abstract: Human communication is inherently multimodal and social: words, prosody, and body language jointly carry intent. Yet most prior systems model human

arXiv:2604.12735v1 Announce Type: new Abstract: LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this p

Best part are retrieval and search details: >Agent queries differ from human queries & what good results means changes too >Parallel queries and ranking are both tools to the same outcome >Top-K preci

`deepagents deploy` now supports user scoped memory! add a user/ directory in your project so each user gets their own writable AGENTS.md, seeded on first deploy and persisted across conversations. yo

arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-

arXiv:2604.12616v1 Announce Type: new Abstract: The rapid evolution of Vision-Language Models (VLMs) has catalyzed unprecedented capabilities in artificial intelligence; however, this continuous modal

arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl

This r/ollama discussion explores the suitability of Google's Gemma 4 models — specifically the 26B Mixture of Experts (MoE) and 31B Dense variants — as MCP (Model Context Protocol) agents for coding

arXiv:2601.06794v2 Announce Type: replace Abstract: Critique-guided reinforcement learning (RL) has emerged as a powerful paradigm for training LLM agents by augmenting sparse outcome rewards with nat

arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic

John Collison / Cheeky Pint: Q&A with ElevenLabs co-founder Mati Staniszewski on how audio models work, the company's business model, the conversational Turing Test, voice agents, and more — Mati Stan

arXiv:2604.12102v1 Announce Type: new Abstract: We introduce compute-grounded reasoning (CGR), a design paradigm for spatial-aware research agents in which every answerable sub-problem is resolved by

arXiv:2604.12231v1 Announce Type: new Abstract: Large language models (LLMs) have transformed AI research thanks to their powerful internal capabilities and knowledge. However, existing LLMs still fai

arXiv:2604.12890v1 Announce Type: cross Abstract: Multimodal deep search agents have shown great potential in solving complex tasks by iteratively collecting textual and visual evidence. However, mana

arXiv:2604.10252v1 Announce Type: new Abstract: Reinforcement learning agent-based simulation (RL-ABS) has become an important tool for electricity market mechanism analysis and evaluation. In the mod

arXiv:2604.11518v1 Announce Type: cross Abstract: Cross-language migration of large software systems is a persistent engineering challenge, particularly when the source codebase evolves rapidly. We pr

arXiv:2604.09601v1 Announce Type: new Abstract: Discovering predictive alpha factors in quantitative finance remains a formidable challenge due to the vast combinatorial search space and inherently lo

This Reddit thread addresses a common challenge for non-developers trying to run a local agentic coding assistant on a MacBook Air M5: while tools like Ollama, VS Code, and OpenCode are the right piec

arXiv:2604.11042v1 Announce Type: new Abstract: Fine-tuning object detection (OD) models on combined datasets assumes annotation compatibility, yet datasets often encode conflicting spatial definition

arXiv:2604.09855v1 Announce Type: new Abstract: The recent advancement of Large Language Models (LLMs) has established their potential as autonomous interactive agents. However, they often struggle in