agents

In this post, we walk through a practical implementation using KDB-X MCP server integration with Amazon Quick, demonstrating how traders and analysts can ask questions using conversational language an

arXiv:2605.31444v1 Announce Type: new Abstract: Reinforcement Learning (RL) enables autonomous agents to learn policies from experience, but realistic problems often involve enormous state spaces, mak

arXiv:2605.30569v1 Announce Type: new Abstract: Robotic manipulation dexterity is often pursued by building increasingly complex high-DoF multifingered hands. While many robotic hands are designed to

arXiv:2605.30667v1 Announce Type: cross Abstract: Software tools for reverse engineering executable binary files, such as Ghidra, enable malware analysts to safely conduct robust static analysis witho

arXiv:2605.31468v1 Announce Type: new Abstract: Scientific research has traditionally been human-intensive, requiring researchers to coordinate literature, ideas, experiments, manuscripts, and review

arXiv:2605.30976v1 Announce Type: cross Abstract: We study stochastic linear bandits under a natural combination of batching and communication constraints: the time horizon is partitioned into batches

arXiv:2605.31256v1 Announce Type: new Abstract: Embodied Large Language Models (LLMs) are increasingly used as reasoning modules in robotic control pipelines to improve human-robot interaction, but th

Harrison Chase compares LangSmith Engine to Tesla's 'Full Self-Driving' moment, suggesting it represents a significant advancement in AI engineering capabilities and automation. The post indicates Lan

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

This post outlines the agent development lifecycle, consisting of four key phases: Build, Test, Deploy, and Monitor. The content covers best practices and methodologies for developing AI agents using

arXiv:2605.30983v1 Announce Type: new Abstract: Despite the remarkable success of multi-modal bird's-eye view (BEV) perception in autonomous driving, current systems exhibit a critical vulnerability:

arXiv:2605.31581v1 Announce Type: new Abstract: The same arguments often need to be evaluated under different external regimes. An agent with influence over the regime has a strategic lever that stand

arXiv:2605.31264v1 Announce Type: new Abstract: LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and in

❄️ Come meet the LlamaIndex Team at Snowflake Summit 2026. It might be chilly in Snow Park ☃️ but the AI infrastructure market is red hot 🔥. Come visit our team at the expo floor and explore how you c

arXiv:2605.30842v1 Announce Type: new Abstract: Context management enables agentic models to solve long-horizon tasks through iterative summarization of previous interaction histories. However, this p

arXiv:2605.31224v1 Announce Type: cross Abstract: The use of Generative AI Conversational User Interfaces (CUI) as a new way to access and analyze data is growing in all sectors, and the industrial on

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:2605.30653v1 Announce Type: new Abstract: Multi-agent LLM systems often treat agreement as evidence: when many agents in a panel give the same answer, that answer is assumed to be more reliable.

Demo2 showcases Qwen's multimodal interactive hybrid agent capabilities, likely demonstrating the integration of multiple data types (text, image, audio, video) with interactive features and hybrid pr

Demo3 showcases Qwen's browser agent capabilities, likely demonstrating an AI system's ability to autonomously interact with web browsers to perform tasks such as navigation, form filling, or informat

arXiv:2605.31119v1 Announce Type: cross Abstract: In robotics, dangers and adversity modes are often embodiment-specific and relative to each agent. A frontier of autonomous mobile robotics is to enab

arXiv:2605.31361v1 Announce Type: cross Abstract: In cooperative multi-agent reinforcement learning (MARL), agents must coordinate with partners whose internal policies and intentions are not directly

While deploying Model Context Protocol (MCP) servers in production, enterprises need fine-grained access control across servers, observability into which teams use which tools, security guarantees aga

arXiv:2605.31064v1 Announce Type: cross Abstract: Large Language Models (LLMs) have significantly advanced online data services, particularly in the domain of financial question answering (FinQA). How

LangSmith's APAC instance now supports Fleet computer use, enabling Fleet agents to access virtual computers for enhanced functionality. This feature allows users in the Asia-Pacific region to leverag

arXiv:2605.31318v1 Announce Type: new Abstract: Modeling an opponent's intent is critical for effective decision-making in non-cooperative, competitive, and general-sum multi-agent reinforcement learn

great look into how Rippling built RipplingAI .@Rippling AI runs on Deep Agents and LangSmith. Here’s how they shipped to millions of users in 6 months. https://www.langchain.com/blog/how-rippling-wen

arXiv:2605.31023v1 Announce Type: new Abstract: This work addresses the problem of autonomous resource management in heterogeneous satellite cluster conducting Earth Observation (EO) missions includin

have manually read 1000s traces since joining LangChain! it’s a great way to learn and understand your agent but completely infeasible to do at agent scale 🙃 engine helps us automate that process so h

Nous Research announced native support for Hermes Agent on Windows, expanding the availability of their Hermes model to Windows-based systems. This development enables Windows users to run Hermes Agen

Hermes from NousResearch is a strong open-source agent harness. This post examines how its runtime loop, context management, tool scoping, session infrastructure, and orchestration patterns map to a m

arXiv:2605.31370v1 Announce Type: new Abstract: Abductive reasoning over knowledge graphs aims to generate logical hypotheses that explain observed entities or facts. Existing controllable hypothesis

i know it's backwards order, but experiment #2: https://x.com/ActiveGraphAI/status/2061106299748909090?s=20 [New Technical Blog Post] In our second longmemeval experiment, we introduce semantic ingest

arXiv:2605.30939v1 Announce Type: new Abstract: Semantic road segmentation is important for autonomous driving, but existing methods suffer severe performance degradation under low-light conditions. M

arXiv:2605.31476v1 Announce Type: new Abstract: End-to-end autonomous driving has emerged as a compelling paradigm for learning planning directly from sensor observations, while recent world-model-bas

arXiv:2605.31514v1 Announce Type: cross Abstract: Much research has been carried out on large language models (LLMs) and LLM-powered agentic workflows. However, many works within the field state emerg

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

In @latentspacepod podcast, I shared my view on video generation, world models, LLMs, agents, continual learning and where the next frontier is. 1. Video models get most of their intelligence from lan

arXiv:2605.31278v1 Announce Type: new Abstract: Reliable evaluation of agentic systems requires unbiased estimates with valid uncertainty, but standard practice navigates between costly human annotati

Introducing Search as Code, our new search architecture for AI agents. It writes Python that calls our search stack directly, instead of looping through function calls one at a time. Available in the

arXiv:2605.30677v1 Announce Type: cross Abstract: Agentic software reverse engineering systems are vulnerable to prompt injection attacks placed into the source code of executable binary files. This r

Join us, @mercor_ai, @Etched, and @AnthropicAI for a one-day hackathon in SF with a 50k top prize. Registrations close on 6/12. We can't wait what to see you build! We're running a 24-hour hackathon J

LangSmith is a development platform designed to build, test, and monitor LLM applications, offering tools for debugging and evaluation to improve AI application quality and reliability. The statement

arXiv:2605.30785v1 Announce Type: new Abstract: LLM agents increasingly face long-horizon tasks such as web search and deep research in real-world applications, where accumulated context can cause lon

arXiv:2605.31365v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on han

arXiv:2605.30656v1 Announce Type: new Abstract: In many practical reinforcement learning environments, observations are far higher-dimensional than the variables that matter for control. In this work,