Knowledge catalogue
arXiv:2607.02255v1 Announce Type: new Abstract: Memory for a long-horizon LLM agent is a contract about what each future decision is allowed to see. The simplest contract appends past observations, to
arXiv:2510.04520v2 Announce Type: replace Abstract: Accurate auto-formalization of theorem statements is essential for advancing automated discovery and verification of research-level mathematics, yet
arXiv:2603.22435v2 Announce Type: replace-cross Abstract: 'Code-as-Policy' considers how executable code can complement data-intensive Vision-Language-Action (VLA) methods, yet their effectiveness as
arXiv:2607.01810v1 Announce Type: cross Abstract: Open-source projects depend on a steady inflow of newcomers. A growing concern is that AI coding agents (tools such as Cursor and Claude Code that wri
arXiv:2602.23056v2 Announce Type: replace Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement learni
arXiv:2607.02436v1 Announce Type: cross Abstract: Agentic coding assistants are increasingly given extra capabilities, such as browser based testing tools and design oriented system prompts, on the as
arXiv:2607.01766v1 Announce Type: new Abstract: LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output. Dynamic
arXiv:2607.01992v1 Announce Type: new Abstract: Large-scale battery energy storage systems (BESSs) require O&M decisions that combine alarms, cell-level measurements, device topology, diagnostic table
arXiv:2607.01061v1 Announce Type: new Abstract: Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transfo
arXiv:2607.00454v1 Announce Type: new Abstract: Agricultural advisory systems face a fundamental tension: static agronomic guidelines offer consistent, evidence-based recommendations, yet remain blind
arXiv:2607.00041v1 Announce Type: cross Abstract: Multi-agent LLM systems can decompose software-engineering work into planning, generation, validation, and repair, but a narrower systems problem rema
arXiv:2607.00972v1 Announce Type: new Abstract: Trustworthy deployment of Agentic Retrieval-Augmented Generation (RAG) systems requires mechanisms for estimating when multi-stage reasoning pipelines m
arXiv:2607.00547v1 Announce Type: cross Abstract: Existing egocentric benchmarks have primarily constructed the egocentric setting from first-person-view data, which makes it difficult to evaluate ego
arXiv:2607.00016v1 Announce Type: cross Abstract: Information localization within massive repositories is a cornerstone of agentic LLM systems. While synthetic data-driven optimization has proven succ
arXiv:2511.03591v2 Announce Type: replace Abstract: Safe multi-agent motion planning (MAMP) under task-induced constraints is a critical challenge in robotics. Many real-world scenarios require robots
arXiv:2607.00407v1 Announce Type: new Abstract: Slide design requires personalizing both deck themes and page layouts. Yet, current AI agent-based methods struggle with fine-grained, page-level design
arXiv:2607.00989v1 Announce Type: cross Abstract: Semantic trajectory analysis has recently emerged as an approach for modeling human movement by capturing implicit patterns and behaviors through sema
arXiv:2607.00283v1 Announce Type: cross Abstract: Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat a
arXiv:2606.31174v1 Announce Type: new Abstract: Production large language-model (LLM) agents are increasingly deployed not as lone problem-solvers but as managers: a main model creates specialized sub
Cross-agent feedback loops are incredibly effective -- for a reason. Check out what @leon2mcp and team at @Bloome_im are building in this space: http://bloome.im Bloome lets you pull Claude, ChatGPT,
arXiv:2606.30694v1 Announce Type: cross Abstract: Traffic signal control at urban intersections inherently introduces stop-and-go behavior, resulting in increased delays and reduced traffic efficiency
arXiv:2606.32025v1 Announce Type: new Abstract: Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for perfor
arXiv:2606.17041v4 Announce Type: replace Abstract: Meta-analysis is a demanding form of evidence synthesis that combines literature retrieval, PI/ECO-guided study selection, and statistical aggregati
arXiv:2606.29727v1 Announce Type: new Abstract: Professional translation is often a team-based process: translators, reviewers, and project managers must coordinate terminology, legal force, and accou
arXiv:2606.28436v1 Announce Type: cross Abstract: Program verifiers play a central role in training coding agents, including selecting trajectories for supervised fine-tuning (SFT) and providing rewar
arXiv:2606.28409v1 Announce Type: cross Abstract: Software-compilable C programs routinely fail to complete the four-stage pipeline of a high-level synthesis (HLS) toolchain -- compilation, C simulati
arXiv:2512.07287v3 Announce Type: replace-cross Abstract: As intents unfold and environments change, multi-turn agents face continuously shifting decision contexts. Although reusing past experience is
arXiv:2606.28841v1 Announce Type: cross Abstract: Large language models are increasingly capable of mathematical reasoning, but the proofs they generate are often unreliable and hard to verify. Intera
arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti
arXiv:2606.28339v1 Announce Type: cross Abstract: Industrial 6G networks require ultra-reliable, low-latency, and energy-efficient connectivity in dynamic and blockage-prone environments, where conven
arXiv:2606.28374v1 Announce Type: new Abstract: LLM agents are increasingly improved without weight updates by evolving a natural-language artifact, such as reflections, workflows, playbooks, cheatshe
arXiv:2606.28343v1 Announce Type: cross Abstract: Retrieval-augmented generative agents rely on retrieval for grounding, yet are typically evaluated on a query-by-query basis. This isolates interactio
arXiv:2606.30266v1 Announce Type: cross Abstract: Motion-language agents must possess the bidirectional capability to both understand human movement (motion-to-text, M2T) and generate it from natural
arXiv:2606.29502v1 Announce Type: new Abstract: Skill memories can improve agentic reinforcement learning by reusing past experience as textual guidance, but retrieved skills are not oracular: they ma
We just made it a lot easier for AI agents to work with your documents. LlamaParse MCP now does more than parse or classify files: it can pull structured data out of contracts, invoices, and reports a
arXiv:2606.29354v1 Announce Type: new Abstract: Chain-of-Thought (CoT) improves large language models (LLMs) on difficult reasoning tasks, but it often incurs long natural-language rationales that are
In this post, we show you how to build an automated claims processing pipeline using two key Amazon Bedrock capabilities: Amazon Bedrock Data Automation for intelligent document extraction from health
Enterprise autonomous AI agents inspect code, run tests, search documents, and operate for extended periods on behalf of users , requiring governance frameworks to control access and actions. The Ente
arXiv:2606.27595v1 Announce Type: new Abstract: Web-agent benchmarks overwhelmingly measure depth -- pinning one obscure answer behind a chain of constraints -- while breadth, exhaustively enumerating
arXiv:2603.04873v3 Announce Type: replace Abstract: Accurate time series forecasting underpins decision-making in many domains, yetconventional ML development often faces data scarcity, distribution s
Many organizations today are floating in a ton of data. This is good for powering AI agents, but less favorable when it comes to identifying which signals from all of that data actually matter. The so
arXiv:2606.26479v1 Announce Type: cross Abstract: Recent work (2024 to 2026) has converged on a strategy for defending tool-using LLM agents against indirect prompt injection: rather than training the
arXiv:2606.26859v1 Announce Type: new Abstract: Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remai
arXiv:2606.26460v1 Announce Type: new Abstract: AI-based scientific automation is increasingly possible by using agents to generate hypotheses, design experiments, and analyze data. Data collection is
arXiv:2606.26298v1 Announce Type: new Abstract: Autonomous AI agents may begin to perform consequential, irreversible actions such as clinical prescribing and production software deployment. This pape
arXiv:2606.27136v1 Announce Type: new Abstract: For LLM agents in multi-step interactive environments, a key challenge is to make effective use of accumulated interaction experience. Existing work has
arXiv:2606.26300v1 Announce Type: new Abstract: A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inverted: as foun
arXiv:2606.25819v1 Announce Type: new Abstract: Large language models are increasingly deployed as agents that solve tasks by interacting with external tool environments. Although recent tool-use benc
LucidLink Corp., the maker of a cloud network-attached storage system based on object storage technology, today extended its distributed file system technology into agentic artificial intelligence wit
arXiv:2602.00585v2 Announce Type: replace Abstract: Information-seeking agents have emerged as a powerful paradigm for knowledge-intensive tasks, yet today's systems remain specialized for the open we
arXiv:2606.25705v1 Announce Type: new Abstract: LLM agents are increasingly being used to automate tasks for users within an open GUI environment. They inevitably encounter screens containing user-sen
OpenAI discusses how AI agents are reshaping workplace processes and productivity by automating complex tasks, handling multi-step workflows, and enabling workers to focus on higher-level decision-mak
arXiv:2606.25447v1 Announce Type: cross Abstract: Tool-integrated LLM agents are often wrapped within a harness: the scaffolding that determines which tools are exposed, how they are described, and wh
TrueFoundry Inc., a startup providing management for artificial intelligence workloads, announced Wednesday that it acquired open-source cloud-agnostic enterprise machine learning platform Seldon Tech
Anthropic's Claude API now supports multiplayer agent capabilities that enable multiple Claude instances to collaborate within Slack, with features for proactive behavior and persistent state manageme
arXiv:2606.24245v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly automate complex tasks by integrating language models with external tools and environments. However, th
Voice artificial intelligence testing startup Coval Inc. revealed today that it has raised 28 million in new funding to expand its platform as more enterprises put voice agents into production. Founde
arXiv:2606.24535v1 Announce Type: new Abstract: Multi-agent LLM environments require robust mechanisms for shared knowledge management. This paper formalizes the fleet-memory problem and identifies fo
arXiv:2606.16821v2 Announce Type: replace Abstract: Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that
arXiv:2606.24129v1 Announce Type: new Abstract: For a wheelchair user, a standard blue line on a map is often a broken promise. While platforms like OpenStreetMap (OSM) successfully capture where a pa