agents

arXiv:2505.21569v3 Announce Type: replace-cross Abstract: Although LLM-based agents are proven to master tool orchestration in scientific fields, particularly chemistry, their single-task performance

arXiv:2604.15840v1 Announce Type: new Abstract: Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent's evolving behavior and le

arXiv:2604.15590v1 Announce Type: cross Abstract: Reinforcement learning is a promising approach to autonomous and adaptive security management in networked systems. However, current reinforcement lea

arXiv:2604.15456v1 Announce Type: new Abstract: Trustworthiness and transparency are essential for the clinical adoption of artificial intelligence (AI) in healthcare and biomedical research. Recent d

developing an agent is a harness problem. deploying an agent is a runtime problem. here's a guide to the runtime capabilities that keep agents running in production and the infrastructure that enables

Devin can manage a team of Devins. Managed Devins run in parallel help break down complex tasks. Each managed session is a full Devin, with its own VM, terminal, browser, and testing infrastructure. T

arXiv:2604.15839v1 Announce Type: new Abstract: Most ATP benchmarks embed the final answer within the formal statement -- a convention we call 'Easy Mode' -- a design that simplifies the task relative

arXiv:2604.15327v1 Announce Type: cross Abstract: Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environme

arXiv:2601.05808v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are expected to be trained to act as agents in various real-world environments, but this process relies on rich a

arXiv:2604.15461v1 Announce Type: cross Abstract: LLM-based simulators offer a promising path for generating complex synthetic data where traditional differentially private (DP) methods struggle with

arXiv:2604.15877v1 Announce Type: new Abstract: As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory

arXiv:2604.15319v1 Announce Type: cross Abstract: Exploratory analysis of high-dimensional data relies on embedding the data into a low-dimensional space (typically 2D or 3D), based on which visualiza

arXiv:2510.13920v2 Announce Type: replace Abstract: Query-focused table summarization requires generating natural language summaries of tabular data conditioned on a user query, enabling users to acce

arXiv:2604.01608v2 Announce Type: replace Abstract: Multi-agent systems (MAS) tackle complex tasks by distributing expertise, though this often comes at the cost of heavy coordination overhead, contex

arXiv:2604.15772v1 Announce Type: new Abstract: Reinforcement learning (RL) often struggles in real-world tasks with high-dimensional state spaces and long horizons, where sparse or fixed rewards seve

good point about another benefit of open memory @hwchase17 Memory being open isn't just about lock in, it's about auditability. If a bad memory gets injected, you need to be able to see it, revoke it,

This post from AI researcher Yohei Nakajima is a motivational message wishing readers a successful week, combined with a brief security reminder to rotate secrets (likely referring to API keys, passwo

how to set up hermes agent step by step. built-in memory, 40+ tools, works on your phone, and what to think of hermes vs openclaw: 1. hermes is a personal AI agent that runs in your terminal. think of

'I am envisioning a harmonious interplay of form and space, where each element finds its rightful place within the visual narrative. The pelican emerges as a central figure, its wings poised in dynami

arXiv:2512.02543v2 Announce Type: replace Abstract: Deploying LLM agents at scale typically requires choosing between quality and cost. Existing cost-reduction approaches fail to preserve agility: the

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:2604.15951v1 Announce Type: new Abstract: Generative AI, particularly Large Language Models, increasingly integrates graph-based representations to enhance reasoning, retrieval, and structured d

arXiv:2604.15713v1 Announce Type: cross Abstract: Type annotations are essential when printing terms in a way that preserves their meaning under reparsing and type inference. We study the problem of c

Kimi K2.6 is now available in Hermes Agent. Simply run `hermes update` and use `hermes model` to select a compatible provider hosting the model! Meet Kimi K2.6: Advancing Open-Source Coding 🔹Open-sour

Kimi K2.6 just entered the chat. > beats gpt 5.4 and opus 4.6 on coding. > open source. open weight. > 3x-5x cheaper. > really good for people running agents. > insane at running long tasks. > we're t

Kimi-K2.6 is a new AI model released through Qoder that achieves state-of-the-art performance in coding tasks and supports long-horizon execution and agent swarms, available at a reduced cost of 0.3x

LangSmith Insights Agent helps Credit Genie interpret feedback from customers at scale, and continuously improve their product. https://www.langchain.com/blog/credit-genie-insights-agent-financial-ass

arXiv:2604.16175v1 Announce Type: new Abstract: Automated 3D radiology report generation often suffers from clinical hallucinations and a lack of the iterative verification found in human practice. Wh

Meet Kimi K2.6 agent - Video hero section, WebGL shaders, real backends. From one prompt. 🔹 Video hero sections - cinematic aesthetic, auto-composited 🔹 WebGL shader animations - native GLSL / WGSL, l

Nice paper combining the strength of Skills and RAG. Most RAG systems retrieve on every query, whether the model needs help or not. This is wasteful when the model already knows the answer, and often

NYC FinTech Week just got an AI track 🗽 Next week we're co-hosting the AI Builders Rooftop Happy Hour with @LinkupAPI — for the people shipping fintech agents, document intelligence, and agentic workf

In this post, we'll show you how to build a complete omnichannel ordering system using Amazon Bedrock AgentCore, an agentic platform, to build, deploy, and operate highly effective AI agents securely

arXiv:2603.00663v4 Announce Type: replace Abstract: The Moving Target Vehicle Routing Problem (MT-VRP) seeks trajectories for several agents that intercept a set of moving targets, subject to speed, t

opus 4.7 dropped last week with two new features: xhigh effort: more compute when you need it task budgets: the model knows its limit and wraps up gracefully, this is a great example of giving the mod

arXiv:2604.15483v1 Announce Type: new Abstract: We present a new robotic foundation model, called {pi}_{0.7}, that can enable strong out-of-the-box performance in a wide range of scenarios. {pi}_{0.7}

arXiv:2602.11327v2 Announce Type: replace-cross Abstract: The rapid development of the AI agent communication protocols, including the Model Context Protocol (MCP), Agent2Agent (A2A), Agora, and Agent

arXiv:2604.15946v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation enables models to segment objects or image regions beyond fixed class sets, offering flexibility in dynamic enviro

arXiv:2604.15347v1 Announce Type: cross Abstract: Autism Spectrum Disorder (ASD) affects more than 75 million people worldwide. However, scalable support for practicing everyday conversation is scarce

some interesting trends in terms of LLM adoption 👀 📊 The latest from the LangSmith Signal: We looked at API call volume and developer adoption trends across LLM providers using LangChain open source t

arXiv:2604.16086v1 Announce Type: cross Abstract: One of the dominant paradigms in self-supervised learning (SSL), illustrated by MoCo or DINO, aims to produce robust representations by capturing feat

The LangSmith Signal report analyzes API call volume and developer adoption trends across major LLM providers, leveraging LangChain's open-source data and observability platform to track usage pattern

arXiv:2604.15468v1 Announce Type: cross Abstract: AI-based systems, currently driven largely by LLMs and tool-using agentic harnesses, are increasingly discussed as a possible threat to software engin

arXiv:2604.15719v1 Announce Type: new Abstract: Many consequential decisions must be made before the relevant outcome is known. Such problems are commonly framed as future prediction, where an LLM age

there’s clearly some confusing conflicts + double-think going on in AI between: 1. Closed labs saying use our harness, it’s naturally post-trained and gets the best out of models by being “in-distribu

arXiv:2411.10446v3 Announce Type: replace-cross Abstract: Recent progress in vision-language models (VLMs) has opened new possibilities for robot task planning, but these models often produce incorrec

arXiv:2510.27617v2 Announce Type: replace Abstract: Automation of Register Transfer Level (RTL) design can help developers meet increasing computational demands. Large Language Models (LLMs) show prom