Search: “agents”

Gary Marcus critiques the marketing of large language model autocomplete systems as 'artificial intelligence,' arguing this terminology misrepresents their actual capabilities. He extends this critici

The terminal hasn’t changed much since the 1970s. What you do with it has. Introducing Devin for Terminal: everything we learned building Devin, now as a local agent, available right in your shell. An

7) Multi-agent design. I loved the design of Cove (they were the acquired by Microsoft). It was more of a whiteboard than tabs or chat threads. I don’t think we’ve cracked the right UI for managing ag

GPT-5.5 is now available in Devin as an Agent Preview! GPT-5.5 has set a new bar for what's possible with Devin. It runs longer and more autonomously than any GPT model we've tested, surfacing bugs no

arXiv:2604.21090v1 Announce Type: cross Abstract: AI governance programmes increasingly rely on natural language prompts to constrain and direct AI agent behaviour. These prompts function as executabl

Tool Attention Is All You Need // Tool Attention Is All You Need // New research proposes a practical fix for the hidden 'MCP tax.' The work introduces a dynamic tool gating mechanism built on an Inte

arXiv:2604.19856v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for generating Register-Transfer Level (RTL) code from natural language specifications, but single-shot gene

arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a

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

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

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

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:2604.15373v1 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:2604.14228v1 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:2604.13630v1 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

⚡ 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

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

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:2604.12102v1 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

Love seeing this open-sourced. Had a great chat with @nicoalbanese10 some weeks ago where he hinted to something like this. Great reference architecture for cloud coding agents. Open Agents gives you

arXiv:2604.11131v1 Announce Type: new Abstract: Reinforcement learning (RL) is one of the most practical ways to learn from real-life use-cases. Motivated from the cognitive methods used by humans mak

arXiv:2604.11734v1 Announce Type: cross Abstract: Closed-loop cooperative driving requires planners that generate realistic multimodal multi-agent trajectories while improving safety and traffic effic

arXiv:2604.09581v1 Announce Type: new Abstract: Evaluating web usability typically requires time-consuming user studies and expert reviews, which often limits iteration speed during product developmen

arXiv:2604.11666v1 Announce Type: cross Abstract: As large language models (LLMs) become the engine behind conversational systems, their ability to reason about the intentions and states of their dial

arXiv:2604.11724v1 Announce Type: new Abstract: The age of artificial intelligence has brought many new possibilities and pitfalls in many fields and tasks. The devil is in the details, and those come

arXiv:2604.11544v1 Announce Type: cross Abstract: Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing appro

arXiv:2604.06111v2 Announce Type: replace Abstract: Existing Agent benchmarks suffer from two critical limitations: high environment interaction overhead (up to 41% of total evaluation time) and imbal