Knowledge catalogue
arXiv:2606.11830v1 Announce Type: new Abstract: Background. Large language models and AI agents are increasingly used to support biomedical research, but native model outputs may omit key analytical s
arXiv:2606.10315v1 Announce Type: cross Abstract: LLM-as-judge is the default instrument for evaluating conversational agents, yet its reliability is almost always reported as agreement with human rat
Artificial intelligence infrastructure startup Relai Inc. said today it has closed on 6.9 million in funding as it bids to ensure the reliability of autonomous AI agents for enterprises. The company a
arXiv:2606.09863v1 Announce Type: new Abstract: LLM agents can fail silently by asserting task completion when the environment state shows otherwise. We study this failure mode, false success, across
arXiv:2606.07904v1 Announce Type: new Abstract: Tool-augmented large language model agents increasingly rely on external APIs, but standard tool schemas describe how to call a tool, not when the tool
arXiv:2606.07489v1 Announce Type: new Abstract: Frontier AI systems are bridging the gap between intelligence and utility by shifting from conversational assistants to autonomous agents that execute t
arXiv:2606.07308v1 Announce Type: new Abstract: We study off-policy evaluation (OPE) under strategic behavior where decision subjects (or agents) respond to a decision maker's policy by strategically
arXiv:2606.06741v1 Announce Type: new Abstract: Self-evolving agents requires adaptation after deployment, but existing approaches assume a usable learning loop, such as curated skills, successful tra
good dev tools are cached intelligence for agents! Token costs are why there will be no saas apocalypse / good dev tools are cached intelligence for agents! The popular theory goes: agents can write c
arXiv:2606.04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles,
Radiant Logic Inc., a platform that provides identity visibility and intelligence, today announced it’s extending its services to agentic artificial intelligence to help companies control and govern t
arXiv:2606.03135v1 Announce Type: new Abstract: Large Language Model (LLM) agents often operate under underspecified user instructions, where latent uncertainty over user intent leads to erroneous too
arXiv:2606.02458v1 Announce Type: new Abstract: Organizations routinely run experiments for A/B testing, yet the data generated from one experiment is underutilized to inform subsequent intervention d
arXiv:2606.01199v1 Announce Type: new Abstract: Large language agents are increasingly used for social simulation, yet it remains unclear whether they can sustain coherent behavior in structured organ
arXiv:2606.00555v1 Announce Type: new Abstract: Structure-based drug design increasingly employs LLM agents to iteratively refine ligands against a target pocket, yet a viable ligand must satisfy two
This post likely discusses how the LangChain framework (which Harrison Chase co-founded) can assist developers in constructing more effective AI agents by providing tools, abstractions, and patterns f
arXiv:2605.30727v1 Announce Type: new Abstract: Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external q
arXiv:2601.20789v3 Announce Type: replace Abstract: Open-weight coding agents should hold a fundamental advantage over closed-source systems because they can specialize to private codebases, encoding
arXiv:2605.31075v1 Announce Type: new Abstract: Long-term memory is essential for multimodal agents to build coherent experience, accumulate world knowledge, and achieve continual learning. However, c
arXiv:2605.31445v1 Announce Type: cross Abstract: In this work we study agents in simulated bargaining scenarios, where a buyer and a seller communicate through a text channel and attempt to negotiate
In a few months, people will start to realize how fundamentally important MCP for agents is. It's not even about connecting tools. There are many ways to do that. It's about the types of abstraction i
arXiv:2605.29397v1 Announce Type: new Abstract: HTML observations in LLM-based web agents are extremely long, and while many reduction methods have been proposed, it remains unclear which methods redu
arXiv:2605.29440v1 Announce Type: cross Abstract: Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on comp
The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in the Gemini API. See how they built an agent that can tackle unstructured documents. 📄↓ 🚀 The team at @
arXiv:2605.27785v1 Announce Type: new Abstract: The fastest-growing data in production today is unstructured text: agent traces, chat logs, reasoning chains, model outputs. People want to analyze it,
Artificial intelligence cloud operator CoreWeave Inc. today announced the launch of a new offering that gives enterprise outfits the ability to deploy AI agents that can learn and improve themselves a
arXiv:2605.28258v1 Announce Type: cross Abstract: Generating a game is not the same as making one that can be played. Despite advances in code generation, existing approaches treat game generation as
arXiv:2605.28158v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used to assist with operations research (OR) modeling, yet existing OR-oriented benchmarks often redu
arXiv:2605.28201v1 Announce Type: new Abstract: Large Language Model (LLM) agents remain vulnerable to safety threats from the external environment, where attackers inject adversarial content into ext
.@AdamRLucek on how we use traces to build evals for production agents. Trace data is literally worth its weight in gold these days, if you know what to do with it! As has been established, creating e
arXiv:2605.25430v1 Announce Type: new Abstract: Coding agents produce rich trajectories while solving software-engineering tasks. To enable agent self-evolution, these trajectories can be distilled in
arXiv:2605.24050v1 Announce Type: cross Abstract: Skill libraries allow LLM agents to load task-specific instructions on demand, letting non-expert users solve domain-specific tasks through natural la
arXiv:2605.24426v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly improved through interaction, yet most self-evolution methods adapt either the policy or the learning
arXiv:2602.08023v3 Announce Type: replace-cross Abstract: Existing benchmarks for LLM-based offensive security agents use isolated, single-target setups with a known vulnerable service and fixed objec
Latent Space episode featuring Ivan Burazin discussing Daytona, a platform or framework that enables AI agents to use computers and interact with software systems autonomously. The discussion likely c
arXiv:2605.21347v1 Announce Type: cross Abstract: Diagnosing failures in LLM agents remains largely manual. Practitioners inspect a small subset of execution traces, form ad-hoc hypotheses, and iterat
streaming from modern agents is pretty complex! especially with - parallel tools / subagents - multimodal content - human in the loop events our new streaming primitives make all of this ergonomic! Ag
arXiv:2605.19260v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have recently emerged as promising backbones for GUI-agent models, where high-resolution GUI screenshots are introduced t
The workforce is no longer purely human — and closing the gap between how companies manage people and how they govern AI agents has become one of the defining operational challenges of the digital wor
i'm excited to open source Active Graph: an event-sourced reactive graph runtime for long-running, agents 🔄🧠 events/logs projects a graph. reactive behaviors react and affect the graph. fork-and-diff
there he goes again, @yoheinakajima blazing the paths to continuously running self aware agents. this and the posts he links are super worth reading. i'm excited to open source Active Graph: an event-
arXiv:2605.19196v1 Announce Type: new Abstract: Deep research agents increasingly automate complex information-seeking tasks, producing evidence-grounded reports via multi-step reasoning, tool use, an
arXiv:2605.19798v1 Announce Type: new Abstract: As Socially Interactive Agents (SIAs) become increasingly integrated into daily life, the ability to calibrate user trust to an agent's actual capabilit
arXiv:2605.17046v1 Announce Type: cross Abstract: Autonomous AI coding agents are becoming a core tool for ML practitioners in industry and research alike. Despite this growing adoption, no standardiz
arXiv:2605.17324v1 Announce Type: cross Abstract: Clarification-seeking behavior is widely regarded as a desirable property of LLM agents, enabling them to resolve ambiguity before acting on underspec
arXiv:2605.18583v1 Announce Type: cross Abstract: Coding agents now run autonomously with shell, file, and network privileges. When a user issues a benign request, the agent sometimes does more than a
arXiv:2605.16895v1 Announce Type: cross Abstract: End-to-end LLM trading agents have moved quickly from research curiosity to a small ecosystem of named systems, including FinCon, FinMem, TradingAgent
Voker, an agent analytics platform for artificial intelligence product teams, today announced it has raised 2.2 million in pre-seed funding from Y Combinator and FundersClub. As more companies push AI
arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex, multi-step tasks such as coding or web-based ques
arXiv:2510.10454v2 Announce Type: replace Abstract: Large language models (LLMs) offer a generalizable approach for modeling patient trajectories, but suffer from the long and noisy nature of electron
Agent risk management is evolving rapidly as AI moves into consequential decision-making arenas, collapsing the boundary between human and machine risk across the enterprise. The dual-threat landscape
arXiv:2605.13950v1 Announce Type: cross Abstract: Autonomous language-model agents are increasingly evaluated on long-horizon tool-use tasks, but existing benchmarks rarely capture the complexity and
arXiv:2605.14205v1 Announce Type: new Abstract: LLM-based web agents can navigate live storefronts, yet they often collapse to a single 'average buyer' policy, failing to capture the heterogeneous and
arXiv:2605.14415v1 Announce Type: cross Abstract: Coding agents powered by large language models are increasingly expected to perform realistic software maintenance tasks beyond isolated issue resolut
arXiv:2605.13360v1 Announce Type: new Abstract: There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applicat
deepagents v0.6 is our biggest release yet!!! it’s all about perf - at the model layer w harness profiles, agent layer w code interpreter, and at scale w streaming and delta channels context hub backe
arXiv:2605.11026v1 Announce Type: cross Abstract: Defenses against indirect prompt injection (IPI) in tool-using LLM agents share two structural weaknesses. First, they all attempt to prevent attacks
arXiv:2605.11695v1 Announce Type: new Abstract: Symbols are shared, but perception is private. We study emergent communication between heterogeneous visual agents through decentralized learning, askin
Agentic AI is changing the way users get work done. Following the success of OpenClaw, the community is embracing new open source agentic frameworks. The latest is Hermes Agent, which crossed 140,000
One of the biggest challenges with agents is that they produce way more than just tokens. Tool calls. State updates. Intermediate reasoning. Subagent progress. File changes. Custom events. Structured