agents

arXiv:2605.15132v1 Announce Type: new Abstract: Autonomous multi-agent systems based on large language models (LLMs) have demonstrated remarkable abilities in independently solving complex tasks in a

arXiv:2605.15187v1 Announce Type: new Abstract: A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large lan

arXiv:2605.15198v1 Announce Type: cross Abstract: Visual reasoning, often interleaved with intermediate visual states, has emerged as a promising direction in the field. A straightforward approach is

arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v

Beau Rothrock had been at @AngelList for two months when he walked into a Redshift-to-Snowflake migration in deep trouble, already two months behind schedule. He had a 5-week window to migrate all 14,

// Beyond Individual Intelligence // One of the more useful multi-agent surveys I've read this year. 200+ papers mapped along three axes: collaboration mechanisms, failure attribution, and self-evolut

arXiv:2605.14892v1 Announce Type: new Abstract: LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use, yet remain limited when tasks require sustained

arXiv:2510.02837v2 Announce Type: replace Abstract: Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory as

Three years of enterprise AI investment, and most companies are still waiting for the payoff. Boomi LP thinks it has found it, unveiling Boomi Companion, a collection of open-source agent skills that

arXiv:2508.02332v3 Announce Type: replace Abstract: The performance of Bayesian optimization (BO), a highly sample-efficient method for expensive black-box problems, is critically governed by the sele

BREAKING: The results are in for Slides Arena... @AnthropicAI and @Zai_org models continue to lead the way in soft-verifiable domains 1st: Opus 4.7 by @AnthropicAI 2nd: Opus 4.7 (Thinking) by @Anthrop

Bring Cava here Soulva being so popular on Doordash is a sign of SF's lack of variety when it comes to quick dining options. Their meats are drier than sand, their kale is rigid and bitter. It's such

Learn about the experimental general-purpose accessibility agent that GitHub is piloting. The post Building a general-purpose accessibility agent—and what we learned in the process appeared first on T

arXiv:2605.13918v1 Announce Type: cross Abstract: Automated game testing is important for verifying game functionality, but it remains a costly and time-consuming process. Manual testing often misses

arXiv:2605.15041v1 Announce Type: new Abstract: Tool use extends large language models beyond parametric knowledge, but reliable execution requires balancing appropriate reasoning depth with strict st

arXiv:2605.14102v1 Announce Type: new Abstract: Autonomous language-model agents increasingly combine planning, tool use, document processing, browsing, code execution, and verification loops. These c

arXiv:2605.14911v1 Announce Type: new Abstract: High-fidelity physics simulation is essential for closing the sim-to-real gap in robotics and complex mechanical systems. However, the computational ove

arXiv:2601.15620v2 Announce Type: replace Abstract: The 1-identification problem is a fundamental pure-exploration problem in multi-armed bandits. An agent aims to determine whether there exists an ar

arXiv:2605.14398v1 Announce Type: new Abstract: World models have emerged as a powerful paradigm for building interactive simulation environments, with recent video-based approaches demonstrating impr

arXiv:2605.15077v1 Announce Type: cross Abstract: Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. U

arXiv:2605.14495v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent fr

arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR)

This post shares feature requests and ideas inspired by experimentation with micro (likely a small language model or tool), credited to another developer. It appears to be a wishlist of desired capabi

“Dependably for LLM agent failures” @hwchase17 Started on this and finding it awesome; also LangSmith engine sparked an idea. The 'Dependabot like for LLM agent failures'. LangSmith Engine gives you t

arXiv:2605.14403v1 Announce Type: new Abstract: Dermatological diagnosis requires integrating fine-grained visual perception with expert clinical knowledge. Although Multimodal Large Language Models (

arXiv:2605.14262v1 Announce Type: new Abstract: As robots become increasingly integrated into everyday environments, intuitive communication paradigms such as natural language and end-user programming

arXiv:2605.14350v1 Announce Type: new Abstract: Multi-task reinforcement learning (MTRL) aims to train a single agent to efficiently optimize performance across multiple tasks simultaneously. However,

arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da

Excited to see SmithDB announcement at Interrupt, our purpose-built distributed database for agent observability! SmithDB is built on top object storage, written in Rust and leverages Apache DataFusio

Fine, you all want to code like this I guess. (Runway's new Agent mode is quite impressive, doing fairly complex story building from just a short text description of what you want. Not error free obvi

arXiv:2605.15181v1 Announce Type: new Abstract: Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetari

arXiv:2605.14501v1 Announce Type: cross Abstract: This paper proposes a fully dynamic Deep Reinforcement Learning (DRL) method for rebalancing dockless bike-sharing systems, overcoming the limitations

arXiv:2605.13874v1 Announce Type: cross Abstract: Autonomous research agents can already run machine learning experiments without human supervision, but many rely on a narrow search strategy: they rep

Go in with expectations that Grok Build is still beta, but improving almost every day Grok Build is amazing. The early beta just dropped for SuperGrok Heavy users and the first real feedback from deve

arXiv:2603.07833v2 Announce Type: replace-cross Abstract: Temporal-difference (TD) learning is highly effective at controlling and evaluating an agent's long-term outcomes. Most approaches in this par

arXiv:2603.21250v2 Announce Type: replace Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former

Great paper discussing agentic search vs. vector search. // Is Grep All You Need? // Pay attention to this on, AI devs. (bookmark it) They find that grep-style text search, when wrapped in the right a

arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m

Had the honor of sharing the stage with the one and only @sydneyrunkle at Interrupt 2026 to talk about Deep Agents. Sign-up for the Managed Deep Agents waitlist today to get early access! https://www.

arXiv:2605.14261v1 Announce Type: new Abstract: How should an agent's performance in a multiagent environment be evaluated when there is a limited sample size or a high cost of running a trial? The AI

@hwchase17 Started on this and finding it awesome; also LangSmith engine sparked an idea. The 'Dependabot like for LLM agent failures'. LangSmith Engine gives you the smoke detector. The natural next

arXiv:2605.14259v1 Announce Type: new Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning. Exis

ICYMI: 1️⃣ LangSmith Engine 2️⃣ SmithDB 3️⃣ Managed Deep Agents 4️⃣ LangSmith Sandboxes: Now Generally Available 5️⃣ Context Hub 6️⃣ LangSmith LLM Gateway 7️⃣ Sandboxes, Prebuilt agents, + free model

arXiv:2605.14851v1 Announce Type: cross Abstract: Operational plan generation and verification are critical for modern complex and rapidly changing battlefield environments, yet traditional generation

arXiv:2605.14612v1 Announce Type: cross Abstract: AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers

arXiv:2605.14455v1 Announce Type: new Abstract: The Intelligence Impact Quotient (IIQ) is a composite metric intended to quantify the depth to which AI systems are integrated into organizational work