Knowledge catalogue
arXiv:2603.02274v2 Announce Type: replace-cross Abstract: Precision oncology is currently limited by the small-N, large-P paradox, where high-dimensional genomic data is abundant but pharmacological r
arXiv:2605.08083v1 Announce Type: new Abstract: Test-time scaling (TTS) has become an effective approach for improving large language model performance by allocating additional computation during infe
arXiv:2604.03675v2 Announce Type: replace Abstract: Agentic search enables language models to solve knowledge-intensive tasks by adaptively acquiring external evidence over multiple steps. Reinforceme
Artificial intelligence customer service platform provider Quiq Inc. today launched a new voice product and refreshed its brand, betting that customer experience teams are ready to move beyond isolate
arXiv:2605.06230v2 Announce Type: replace Abstract: As large models evolve from conversational assistants into autonomous agents, challenges increasingly arise from long-horizon decision making, tool
This post describes a project where the developer created an autonomous AI agent capable of modifying and executing its own source code across a 7-day development period, integrating multiple language
arXiv:2605.03537v1 Announce Type: cross Abstract: This paper presents a modular AI agentic skill pipeline for automating subject indexing with Library of Congress Subject Headings (LCSH). Subject inde
arXiv:2502.10148v3 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) struggles with sample efficiency, interpretability, and generalization. While Large Language M
arXiv:2605.03242v1 Announce Type: new Abstract: Tool-using agent systems powered by large language models (LLMs) are increasingly deployed across web, app, operating-system, and transactional environm
arXiv:2605.03383v1 Announce Type: new Abstract: Lithology classification aims to infer subsurface rock types from well-logging signals, supporting downstream applications like reservoir characterizati
arXiv:2605.03604v1 Announce Type: cross Abstract: This paper asks whether large language models (LLMs) can be used to study the strategic foundations of conflict and cooperation. I introduce LLMs as e
arXiv:2605.04019v1 Announce Type: new Abstract: AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a
arXiv:2605.03034v1 Announce Type: new Abstract: Agentic systems involved in high-stake decision-making under adversarial pressure need formal guarantees not offered by existing approaches. Motivated b
arXiv:2605.01740v1 Announce Type: cross Abstract: An agentic-AI runtime issues tool calls, sends messages, and actuates devices on behalf of an LLM. Catching the four ways an action can diverge from i
arXiv:2605.01394v1 Announce Type: cross Abstract: Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Alth
arXiv:2605.01507v1 Announce Type: new Abstract: Prior studies report that partial driving automation can increase the cognitive demands on human drivers. This effect largely arises from human drivers'
arXiv:2605.01471v1 Announce Type: cross Abstract: Maintaining reliable UI test suites in large-scale enterprise applications is a persistent and costly challenge. We present an industrial case study o
arXiv:2605.00914v1 Announce Type: cross Abstract: Multi-agent debate, where teams of LLMs iteratively exchange rationales and vote on answers, is widely deployed under the assumption that peer review
arXiv:2605.01970v2 Announce Type: cross Abstract: Memory systems enable otherwise-stateless LLM agents to persist user information across sessions, but also introduce a new attack surface. We characte
arXiv:2605.02463v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly used to solve complex tasks through decomposition, debate, specialization, and ensemble reasoning. However, t
arXiv:2601.06034v1 Announce Type: cross Abstract: Software testing is critical in the software development lifecycle, yet translating requirements into executable test scripts remains manual and error
arXiv:2605.01675v1 Announce Type: cross Abstract: Constraint Programming (CP) is a powerful paradigm for solving combinatorial problems, yet translating natural language problem descriptions into exec
arXiv:2605.01299v1 Announce Type: new Abstract: Geometric Algebra (GA) presents challenges to learners due to its highly abstract mathematical structure and complex operational rules, as translating a
arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i
arXiv:2508.12232v3 Announce Type: replace-cross Abstract: Issue-to-commit link recovery in software repositories is fundamental to software traceability and project management, yet it remains a challe
arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding
arXiv:2605.02168v1 Announce Type: cross Abstract: Language model (LM)-based agents have demonstrated promising capabilities in automating complex tasks from natural language instructions, yet they con
arXiv:2605.01416v1 Announce Type: cross Abstract: The increasing scale and complexity of online platforms raises critical policy questions around harmful content, digital well-being, and user autonomy
The AI Engineer World's Fair is a conference event featuring talks on emerging AI research and engineering topics including autoresearch systems, advanced memory architectures, world models, tokenizat
arXiv:2604.27725v1 Announce Type: cross Abstract: A long-standing challenge in economics lies not in the lack of intuition, but in the difficulty of translating intuitive insights into verifiable rese
arXiv:2604.26962v1 Announce Type: cross Abstract: Education represents one of the most promising real-world applications for Large Language Models (LLMs). However, conventional tutoring systems rely o
arXiv:2604.27309v1 Announce Type: new Abstract: Clinical AI systems require not just point-in-time evaluation but continuous governance: the ongoing practice of monitoring, evaluating, iterating, and
arXiv:2604.27351v1 Announce Type: new Abstract: Agentic large language model systems have demonstrated strong capabilities. However, their reliance on language as the universal interface fundamentally
arXiv:2604.27150v1 Announce Type: new Abstract: Autonomous crypto trading systems often spend most of their design effort on finding entries, while exits are left to fixed rules that are rarely tested
arXiv:2602.07408v2 Announce Type: replace Abstract: Predicting gene regulation responses to biological perturbations requires reasoning about underlying biological causalities. While large language mo
arXiv:2604.28093v1 Announce Type: new Abstract: Terminal-agent benchmarks have become a primary signal for measuring the coding and system-administration capabilities of large language models. As the
In corporate parlance, any metric on a chart that shows rapid, significant growth over a short period of time is known as a “hockey stick.” On Wednesday, Stripe Inc. Chief Executive Patrick Collison s
arXiv:2604.25980v1 Announce Type: cross Abstract: In the context of quantum secure scenarios, existing research on mobile edge devices and intelligent computing and edge (ICE) systems based on the Non
Aviatrix Inc. today announced the launch of a new platform designed to contain artificial intelligence agents and enforce security controls and communications across AI workloads without changing AI a
arXiv:2604.24929v1 Announce Type: new Abstract: Agent benchmarks remain largely English-centric, while their multilingual versions are often built with machine translation (MT) and limited post-editin
arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev
arXiv:2604.24549v1 Announce Type: cross Abstract: Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting thr
arXiv:2508.19679v2 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have enabled mobile agents to perceive and interact with real-world mobile environments based on hu
arXiv:2506.20332v4 Announce Type: replace Abstract: Vision-language model-based mobile agents have gained the ability to understand complex instructions and mobile screenshots, benefiting from reinfor
arXiv:2512.15930v2 Announce Type: replace-cross Abstract: Intrinsically disordered proteins (IDPs) represent crucial therapeutic targets due to their significant role in disease -- approximately 80% o
arXiv:2509.13021v2 Announce Type: replace-cross Abstract: This work introduces xOffense, an AI-driven, multi-agent penetration testing framework that shifts the process from labor-intensive, expert-dr
arXiv:2604.22256v1 Announce Type: cross Abstract: Goal recognition aims to infer an agent's goal from observations of its behaviour. In realistic settings, recognition can benefit from exploiting hier
arXiv:2604.22191v1 Announce Type: cross Abstract: In agentic workflows, LLMs frequently process retrieved contexts that are legally protected from further training. However, auditors currently lack a
Nous Research announced that their Hermes Agent repository has surpassed Anthropic's Claude Code repository in popularity metrics, likely referring to GitHub stars or similar engagement measures. This
arXiv:2604.22558v1 Announce Type: cross Abstract: As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to complex navigation. While Reinforcement Learni
Gary Marcus critiques the marketing of large language model autocomplete systems as 'artificial intelligence,' arguing this terminology misrepresents their actual capabilities. He extends this critici
The terminal hasn’t changed much since the 1970s. What you do with it has. Introducing Devin for Terminal: everything we learned building Devin, now as a local agent, available right in your shell. An
7) Multi-agent design. I loved the design of Cove (they were the acquired by Microsoft). It was more of a whiteboard than tabs or chat threads. I don’t think we’ve cracked the right UI for managing ag
GPT-5.5 is now available in Devin as an Agent Preview! GPT-5.5 has set a new bar for what's possible with Devin. It runs longer and more autonomously than any GPT model we've tested, surfacing bugs no
arXiv:2604.21090v1 Announce Type: cross Abstract: AI governance programmes increasingly rely on natural language prompts to constrain and direct AI agent behaviour. These prompts function as executabl
Tool Attention Is All You Need // Tool Attention Is All You Need // New research proposes a practical fix for the hidden 'MCP tax.' The work introduces a dynamic tool gating mechanism built on an Inte
arXiv:2604.19856v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for generating Register-Transfer Level (RTL) code from natural language specifications, but single-shot gene
arXiv:2604.19839v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong perception and reasoning abilities for instruction-following embodied agents. However, despite these a
arXiv:2604.20486v1 Announce Type: new Abstract: Training multimodal agents via reinforcement learning for knowledge-intensive visual reasoning is fundamentally hindered by the extreme sparsity of outc
zero shot Kimi K2.6, go try it out its a good model sir! this is @Kimi_Moonshot running on @togethercompute, @opencode harness prompt below👇 Media Introducing Kimi K2.6 from @Kimi_Moonshot, a multimod