Knowledge catalogue
arXiv:2609.01679v1 Announce Type: new Abstract: The ability of AI systems to improve their behavior during deployment is becoming increasingly important. As inference moves beyond the static execution
arXiv:2512.10534v4 Announce Type: replace Abstract: Large language model (LLM) agents exhibit strong mathematical problem-solving abilities and can even solve International Mathematical Olympiad (IMO)
arXiv:2609.02605v1 Announce Type: new Abstract: The Mini-Girona Intervention Autonomous Underwater Vehicle (I-AUV) represents an advancement in accessible underwater robotics, designed to bridge the g
Artificial intelligence has moved from a curiosity in the threat landscape to a working part of the intrusion, and agentic adversaries have infiltrated extortion campaigns, espionage operations and ha
arXiv:2609.02122v1 Announce Type: new Abstract: As large language model (LLM) agents shift from tools to participants in human groups, a fundamental question for collective behavior is how their growi
arXiv:2505.22451v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have made significant progress in mathematical capabilities in recent times. However, these successes have been primar
arXiv:2609.02487v1 Announce Type: new Abstract: The ability to move stably over terrain with varying slopes and textures is essential for mobile agricultural robots operating in complex and dynamic en
Banger paper from BAAI. If you are building research agents, this one is worth your time. (bookmark it) They find that adding skills scores 134.3% higher on MLE-bench, 34.4% higher on PaperBench, 9.2%
Learn best practices for building production-grade, agent-based business process automations with Amazon Quick Automate: choosing the right process, designing focused agents, combining them with deter
arXiv:2410.10136v2 Announce Type: replace-cross Abstract: In customer contact centers, human agents often struggle with long average handling times (AHT) due to the need to manually interpret queries
arXiv:2609.02750v1 Announce Type: new Abstract: Multi-agent LLM systems commonly use an orchestrator to decompose a task for a team of workers and then improve through textual reflection. Despite stro
Check out the blog here: https://www.llamaindex.ai/blog/introducing-turbo-our-fastest-extraction-tier If you're interested in trying it out, come sign up for a LlamaParse account: https://cloud.llamai
arXiv:2609.01992v1 Announce Type: new Abstract: Agent evaluations face two distinct evidentiary questions: whether a reported claim is recomputable from retained evidence (sufficiency), and whether th
arXiv:2609.02264v1 Announce Type: new Abstract: Adapting the communication topology of an LLM multi-agent system to each query improves both accuracy and efficiency, yet current designers treat this a
arXiv:2609.01663v1 Announce Type: cross Abstract: Agentic AI systems are increasingly deployed to process sensitive data at inference time, such as healthcare records or financial documents assembled
An AI agent doesn’t need to be malicious to cause damage. It just needs to reason its way into the wrong system, the way a well-meaning agent handling a finance report might decide it needs a code rep
arXiv:2603.10248v2 Announce Type: replace Abstract: Teach and Repeat (T&R) topometric navigation enables robots to autonomously repeat previously traversed paths without relying on GPS, making it well
Document extraction just got a new gear. ⚡️ Introducing Turbo mode for Extract, our fastest way yet to pull structured data from documents. It runs roughly 4× faster than our Cost Effective Tier at co
arXiv:2609.01873v1 Announce Type: new Abstract: Multi-agent AI systems improve inference by spawning agents and synthesizing reports. But another agent is not another observation: apparently independe
arXiv:2510.18699v2 Announce Type: replace-cross Abstract: Recent surges in LLM-driven intelligent systems largely overlook decades of foundational multi-agent systems (MAS) research, resulting in fram
arXiv:2609.02106v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly explore many candidate states of relational data in parallel, each of which should remain isolated, rep
Good measurement work on whether retrieved agent skills actually help. They report that agent skills that lift your aggregate score can be hurting every task they touch. The usual way of checking comp
arXiv:2609.01617v1 Announce Type: cross Abstract: Getting accurate, grounded answers out of large enterprise document repositories is a difficult problem. Dense vector retrieval alone frequently perfo
arXiv:2609.02056v1 Announce Type: new Abstract: Scientific knowledge graphs organize entities and relations extracted from scientific literature, but they remain inherently incomplete. Missing typed l
Impressive tool to explore frontier AI capabilities. Martian's AI Frontier lets you compare 44 LLMs by measured cost, quality, and reliability, then see how routing and repeated sampling change the fr
arXiv:2609.02002v1 Announce Type: cross Abstract: Guideline-consistent semantic segmentation requires more than category recognition, as real-world labeling policies demand fine-grained, task-specific
Introducing K2 Horizon: a connected fleet of six foundation models ranging from 0.9 billion to 375 billion parameters. - Frontier performance: Across coding and agentic tasks, K2 Horizon delivers top-
arXiv:2609.02077v1 Announce Type: new Abstract: Accurate 3D ship detection in maritime environments is critical for autonomous navigation, yet remains challenging due to large-scale vessel variations,
arXiv:2609.02350v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires an embodied agent to follow natural-language instructions in unseen environments. Recent progress has been lar
arXiv:2609.02094v1 Announce Type: new Abstract: LLM-based multi-agent systems have shown strong performance on complex tasks, yet continual improvement from interaction experience remains challenging.
An agent that works in a notebook is not an agent in production. This post walks through migrating a LangGraph customer support agent to Amazon Bedrock AgentCore in two stages: onto Runtime, Gateway,
arXiv:2609.02057v1 Announce Type: new Abstract: Reliable web-agent monitoring is difficult when model-internal uncertainty signals such as token logits are unavailable. In this work, we study prefix-l
arXiv:2609.01618v1 Announce Type: cross Abstract: Telecom Service and Network Operations Centers (SNOCs) rely on large collections of cloud documents, including Standard Operating Procedures (SOPs), v
arXiv:2609.01971v1 Announce Type: new Abstract: AI is rapidly advancing neuroscience, yet many laboratories fail to fully unleash its potential due to significant interdisciplinary barriers. While pre
arXiv:2609.02149v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly evolving from conversational assistants into agents capable of operating external digital environments.
arXiv:2609.02575v1 Announce Type: new Abstract: This paper investigates how a production transitional autonomous vehicle (tAV) develops and executes mandatory lane-change decisions. Using 150 controll
arXiv:2609.01622v1 Announce Type: cross Abstract: The rise of agentic AI has catalyzed a shift toward self-iterating systems, opening new frontiers for the autonomous optimization of production recomm
Research doesn’t end in right or wrong, but in insights that lead to more questions. General-purpose models aren’t fit for research because they don’t know customers’ workflows. @quadrillionlabs train
arXiv:2609.02250v1 Announce Type: cross Abstract: Ride-sharing, which allows multiple passengers with different origin-destination (OD) pairs to share a single vehicle, is a challenging operational pr
arXiv:2607.10372v2 Announce Type: replace-cross Abstract: The transition of autonomous mobile robots from controlled industrial settings to dynamic, human-centric environments, such as manufacturing,
As agentic AI moves from experimentation toward enterprise deployment, the challenge is figuring out how agents can work together, connect to the systems and data they need, and operate safely across
arXiv:2609.02780v1 Announce Type: cross Abstract: Streaming video understanding is a critical capability for real-world applications, including embodied intelligence, autonomous driving, industrial mo
arXiv:2608.25202v3 Announce Type: replace-cross Abstract: Spec-Driven Development (SDD) is a fast-emerging practice in which a structured natural-language specification, written by a developer, or (mo
arXiv:2609.02364v1 Announce Type: cross Abstract: Existing Human-Robot Interaction (HRI) literature has focused on identifying and structuring errors, failures, conflicts, and knowledge issues (called
arXiv:2609.02341v1 Announce Type: new Abstract: Vision-Language-Action models (VLAs) have shown strong potential in autonomous driving by leveraging multimodal pretraining for instruction following, v
arXiv:2512.05211v2 Announce Type: replace Abstract: Morphing aerial robots have the potential to transform autonomous flight, enabling navigation through cluttered environments, perching, and seamless
arXiv:2609.02322v1 Announce Type: cross Abstract: The first problem of modeling the world is not just estimating the right parameters or causal structure, but deciding what should be represented at al
arXiv:2609.01814v1 Announce Type: new Abstract: Information sharing can improve a pooled estimate while eliminating independent rescue actions. This paper separates those effects in exact finite disco
arXiv:2608.27984v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) have recently moved from static workflows toward dynamically generated collaboration topologies. However, existing topolog
zai earnings transcript was a really good read, a list of interesting points (mostly verbatim from the transcript): * Chat → Coding → Agent → Cowork → Autonomous AI * What truly matters is who can con
arXiv:2609.00769v1 Announce Type: new Abstract: This letter presents a compact two-degree-of-freedom (DoF) robotic finger with a flexion-selective passive continuously variable transmission (CVT) to a
arXiv:2609.00060v1 Announce Type: cross Abstract: Agent payment protocols are emerging as a key transaction layer for autonomous commerce, enabling AI agents to purchase goods and services and execute
arXiv:2609.00322v1 Announce Type: cross Abstract: Can an artificial intelligence (AI) generate a scientific hypothesis outside a human collaborator's active hypothesis space (AHS), and can human-AI re
arXiv:2601.04243v2 Announce Type: replace-cross Abstract: This paper presents a hybrid insider threat detection framework for enterprise environments, integrating multi-agent simulation, layered SIEM
// Agent Zero Memory // This work separates three things that agent memory systems usually collapse into one. If you build agents with long-term memory, this memory design is a worth a read. Here is h
arXiv:2609.01045v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities as powerful components in agentic systems, enabling sophisticated reasoning and c
arXiv:2609.00731v1 Announce Type: new Abstract: Recent advances in LLM agents enable a new paradigm for asset pricing, which we call Agentic Empirical Asset Pricing (AEAP): systems that autonomously c
arXiv:2609.01289v1 Announce Type: new Abstract: Hyperspectral unmixing is a key task in remote sensing that aims to decompose mixed pixels in hyperspectral images into their constituent material signa
arXiv:2609.00795v1 Announce Type: cross Abstract: Computational materials science has traditionally delegated algorithmic tasks to computers while leaving scientific judgments to humans. We argue that
arXiv:2603.29093v3 Announce Type: replace-cross Abstract: LLM agents rerun full reasoning for every task, even one they solved moments earlier. We introduce extbf{APEX-EM}, a non-parametric experience