Knowledge catalogue
arXiv:2605.24785v1 Announce Type: new Abstract: Recent advances in multimodal web agents often rely on increased inference-time computation, including rollout search, verifier passes, offline skill di
arXiv:2605.24218v1 Announce Type: new Abstract: Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how human
arXiv:2605.24069v1 Announce Type: cross Abstract: The rise of tool-using Large Language Model (LLM) agents, standardized by protocols like the Model Context Protocol (MCP), has unlocked unprecedented
arXiv:2605.23193v1 Announce Type: cross Abstract: Gardening is critical to support well-being, cultural continuity, and food autonomy, yet existing digital tools often provide generic advice that over
arXiv:2605.20618v1 Announce Type: new Abstract: Although Vehicle Routing Problems (VRP) are essential to many real-world systems, they remain computationally intractable at scale due to their combinat
arXiv:2605.20200v1 Announce Type: cross Abstract: This article presents a multimodal emotion recognition module integrated into a proactive Socially Interactive Agent (SIA) powered by generative artif
arXiv:2605.20874v1 Announce Type: new Abstract: Enterprise agents are increasingly expected to operate autonomously across tools and interfaces, yet production deployments require governance by constr
software security is a hot topic right now timely podcast with @cogent_security on building agents for cyber defense Great conversation on the Max Agency podcast with @cogent_security Co-Founder + CTO
Bitwarden acknowledges Nous Research for collaboration on security initiatives that extend to AI agents, emphasizing inclusive security practices. The post suggests a partnership or joint effort betwe
This is one of the things I dislike about managed agents. Is it the best DX? yes. Is it now much, much more usable because it's bring your own sandbox? yes (most startups now have Sandbox credits and
Agent streaming has outgrown token deltas. Real apps need to render tools, state, subagents, media, interrupts, and reconnects without parsing a firehose of raw events. The new @LangChain streaming pr
arXiv:2605.20833v1 Announce Type: new Abstract: Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of person
'You actually don't have too many PRs. You have too many bad PRs.' @dexhorthy on how agents write fast, but the intellectual burden of judging the code still lands on a human reviewer. A perfect PR is
arXiv:2605.18930v1 Announce Type: cross Abstract: Memory-augmented large language model (LLM) agents use iterative reflection and self-evolution to solve complex tasks, but these mechanisms introduce
arXiv:2605.19932v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate over long and recurring external contexts, like document corpora and code repositories. Across in
Exa, a search lab focused on organizing web data for AI agents, announced a Series C funding round of 250 million at a 2.2 billion valuation, led by venture capital firm Andreessen Horowitz (a16z). Th
arXiv:2605.19447v1 Announce Type: new Abstract: Reinforcement learning can train LLM agents from sparse task rewards, but long-horizon credit assignment remains challenging: a single success-or-failur
arXiv:2510.07799v2 Announce Type: replace-cross Abstract: The efficiency of multi-agent systems driven by large language models (LLMs) largely hinges on their communication topology. However, designin
arXiv:2605.17554v1 Announce Type: new Abstract: Frontier deep research agents (DRAs) plan a research task, synthesize across documents, and return a structured deliverable on demand. They are being de
arXiv:2605.17873v1 Announce Type: cross Abstract: Training long-horizon LLM agents with reinforcement learning is challenging because sparse outcome rewards reveal whether a task succeeds, but not whi
Yohei Nakajima discusses his exploration of stateful agents and concludes that current implementations have not yet achieved what the concept truly entails, suggesting the field is still in early stag
arXiv:2605.17526v1 Announce Type: cross Abstract: As autonomous coding agents become capable of handling increasingly long-horizon tasks, they have gradually demonstrated the potential to complete end
arXiv:2605.18693v1 Announce Type: new Abstract: As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether t
arXiv:2504.07347v3 Announce Type: replace-cross Abstract: As demand for Large Language Models (LLMs) and AI agents grows rapidly, optimizing systems for efficient LLM inference becomes critical. While
This post explores conceptual parallels between classical distributed systems design patterns—such as actor models and reactive blackboard architectures—and their potential application to LLM agent de
announcing deepagents v0.6, our biggest release yet! it’s all about performance: at the model layer w harness profiles, agent layer w code interpreter, and at scale w streaming and delta channels cont
arXiv:2605.15315v1 Announce Type: new Abstract: LLM-powered coding agents spend the majority of their token budget reading repository files, yet much of the retrieved code is irrelevant to the task at
Nebius and @LangChain have partnered to integrate Nebius Token Factory with LangChain's Deep Agents. The integration, combined with LangChain's existing Tavily integration, gives teams building on Lan
Singapore's head of AI Govtech estimates the country will have 1.3 billion AI agents deployed within the next two years and is actively developing infrastructure to support this expansion. This sugges
Interesting interpretability paper on tool-using agents. The authors probe hidden states and find the model often recognizes it should call a tool, but fails to actually call one. The mismatch ranges
arXiv:2605.14133v1 Announce Type: new Abstract: Interactive agent benchmarks face a tension between scalable construction and realistic workflow evaluation. Hand-authored tasks are expensive to extend
arXiv:2504.11703v3 Announce Type: replace-cross Abstract: AI agents interact with external environments through tool calls, exposing them to attacks like indirect prompt injection that can trigger una
This article likely provides practical advice on how to effectively give feedback to AI agents or autonomous systems, covering techniques for improving agent performance through constructive feedback
arXiv:2605.12507v1 Announce Type: cross Abstract: While Large Language Model (LLM) multi-agent systems (MAS) offer a transformative approach to simulating human behavior in complex systems, it remains
Great move. If you’re building agents, so much time is spent engineering your way through traces. And then comes the hard to rapidly iterate and figure out the changes needed. 🚀Launching: LangSmith En
if you're an artist or creative wondering how to use agents to accelerate your work, or skeptical that they can: please stop what you are doing and look at the 6 examples in this thread The Hermes Age
arXiv:2605.13579v1 Announce Type: new Abstract: Assistive agents for Blind and Visually Impaired (BVI) users require accessibility alignment as a first-class design objective. Despite rapid progress i
the future intelligent agents will learn and grow with your team over ultra long timescales 🕰️ that research direction centers around Continual Learning LangSmith is the data layer that helps us under
arXiv:2602.16246v3 Announce Type: replace Abstract: Interactive large language model (LLM) agents operating via multi-turn dialogue and multi-step tool calling are increasingly used in production. Ben
The dual-threat landscape of enterprise AI security is coming into focus. The same autonomous agents transforming workforce productivity are also expanding the attack surface — and most organizations
Coming up at Interrupt: 🎙️ How @clay scales their GTM Engineering agents with Head of AI @JeffBarg. 🎙️ @ummadisetti and @kordelfrance on how @Toyota Motor North America equipped 56,000 employees with
Cursor highlights that companies like Decagon, Amplitude, BILT, and Snyk leverage development environments within Cursor to enable AI agents to complete tasks independently from start to finish. This
arXiv:2605.11051v1 Announce Type: cross Abstract: LLM-based Software Engineering agents face a critical bottleneck: context length limitations cause failures on complex, long-horizon tasks. One promis
arXiv:2605.11225v1 Announce Type: cross Abstract: Large language model (LLM)-based agents frequently generate seemingly coherent plans that fail upon execution due to infeasible actions, constraint vi
arXiv:2605.08426v1 Announce Type: cross Abstract: Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI s
arXiv:2605.10832v1 Announce Type: new Abstract: Multimodal deep search requires an agent to solve open-world problems by chaining search, tool use, and visual reasoning over evolving textual and visua
arXiv:2605.07926v1 Announce Type: new Abstract: As LLM-based agents increasingly rely on external tools, it is important to evaluate their ability to sustain tool-grounded reasoning beyond familiar wo
arXiv:2605.07110v1 Announce Type: new Abstract: Computer-use agents(CUAs)are moving frombounded benchmarks toward real software environments, wherethey operate browsers, desktops, mobile applications,
arXiv:2605.07161v1 Announce Type: new Abstract: AI agents are increasingly used to diagnose and mitigate failures in production systems, known as agentic Site Reliability Engineering (SRE). Current SR
arXiv:2506.21582v5 Announce Type: replace-cross Abstract: Text analytics has traditionally required specialized knowledge in Natural Language Processing (NLP) or text analysis, which presents a barrie
Harrison Chase suggests that AI agents designed to handle knowledge work tasks will probably require browser capabilities to effectively access and interact with web-based information and resources. T
My favourite new stack: Agents + MCP + Markdown + HTML “Files over apps” is a vibe! LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis ca
one way to view langsmith is as a platform for the whole org to collaborate on building agents helps speed up that feedback loop between different personas @hwchase17 the tooling side is maturing fast
arXiv:2512.04388v5 Announce Type: replace Abstract: Powerful large language models (LLMs) from different providers have been expensively trained and finetuned to specialize across varying domains. In
arXiv:2605.04984v1 Announce Type: cross Abstract: Long-horizon LLM agents depend on intermediate information-gathering turns, yet training feedback is usually observed only at the final answer, becaus
Anthropic is building out their managed agents platform, adding Dreaming (memory) and Outcomes (rubrics). The idea I'm wrestling with: how differentiated are these platform features really? I initiall
arXiv:2511.20657v2 Announce Type: replace-cross Abstract: The development of agents with emotional intelligence is becoming increasingly vital due to their significant role in human-computer interacti
arXiv:2605.01783v1 Announce Type: new Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a se
arXiv:2605.01329v1 Announce Type: new Abstract: In-group favoritism refers to the phenomena of favoring members of one's in-group over out-group members and is widely observed in numerous social coope
arXiv:2605.03596v1 Announce Type: cross Abstract: Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a