3,694 items tracked: 32 reported by two or more outlets, the rest by a single source. Most-corroborated first.
arXiv:2506.21129v3 Announce Type: replace-cross Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation, yet global navigation satellite system (GNSS) spoofing…
arXiv:2602.04692v3 Announce Type: replace-cross Abstract: Referring Multi-Object Tracking (RMOT) aims to track specific targets based on language descriptions, playing a vital role in interactive AI systems such as robot…
arXiv:2603.14371v3 Announce Type: replace-cross Abstract: Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, from shared observation…
arXiv:2603.25063v2 Announce Type: replace-cross Abstract: Recent agentic systems demonstrate that large language models can generate complex codebases from natural language prompts.
arXiv:2604.22560v2 Announce Type: replace-cross Abstract: Graph Visual Question Answering (GVQA) for autonomous driving organizes reasoning into ordered stages, namely Perception, Prediction, and Planning, where planning…
arXiv:2605.00557v2 Announce Type: replace-cross Abstract: Scientific discovery is an extended process of ideation -- surveying prior work, forming hypotheses, and refining reasoning -- yet existing LLM research agents tr…
arXiv:2606.03163v5 Announce Type: replace-cross Abstract: This yellow paper describes the technical architecture of OpenAgenet / OAN.
arXiv:2606.04806v2 Announce Type: replace-cross Abstract: LLMs and agentic systems are increasingly deployed in social environments, making normative competence critical for safe and appropriate behavior.
arXiv:2606.04970v2 Announce Type: replace-cross Abstract: Proactive multimodal assistants must decide when guidance is needed and what to say, while tracking progress through extended procedures and helping users recover…
arXiv:2606.07943v3 Announce Type: replace-cross Abstract: Large language model agents use skills that package reusable instructions, code, and resources.
arXiv:2606.10173v2 Announce Type: replace-cross Abstract: On-device inference reduces exposure to remote infrastructure, but it does not establish privacy for an operating-system assistant that aggregates cross-applicati…
arXiv:2606.18831v2 Announce Type: replace-cross Abstract: Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that must reason over length…
arXiv:2607.03926v2 Announce Type: replace-cross Abstract: Synthetic tabular data support use cases like data sharing, model development under access restrictions, and rapid prototyping of analytical workflows.
arXiv:2607.12723v2 Announce Type: replace-cross Abstract: Container filesystem isolation depends on safely resolving container-controlled paths during privileged host-container interactions.
arXiv:2607.19450v4 Announce Type: replace-cross Abstract: Large-scale online reinforcement learning (RL) is the predominant means of eliciting advanced abilities including long-term reasoning and agentic tool use in larg…
arXiv:2607.23532v3 Announce Type: replace-cross Abstract: Swarms of LLM-assisted autonomous robots are increasingly proposed for cooperative intelligence, surveillance, and reconnaissance (ISR) in contested environments.
arXiv:2608.02660v3 Announce Type: replace-cross Abstract: Advanced AI assistants engage users in extended interactions across a widening range of roles, including advice, decision support, collaboration, learning, emotio…
arXiv:2608.07531v4 Announce Type: replace-cross Abstract: Search-augmented language agents should retrieve external information only when necessary and ground their answers in retrieved evidence.
arXiv:2608.16539v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation, archival ind…
Cerebras CEO Andrew Feldman predicts a future where personal AI assistants become as commonplace as household appliances, running partly on local devices and partly in the cloud.
Our first robotics pod with Dyna’s Chief Scientist on their big bet on World Action Models & the Next Frontier of Physical AI
Enterprise applications have become increasingly demanding.
Geordie's tests recorded 155 activity traces and multiple subagents after dot was given read-only permissions
Learn how the AWS Generative AI Innovation Center Partner Agent Factory and Anchor Browser built AI agents that autonomously pay for x402-protected web resources and APIs.
More AI agents will soon be able to browse and purchase from Shopify listings, marking an expansion of the company's agentic commerce ambitions.
Square is launching new hardware: a big kiosk for ordering things that has a touchscreen and lets you talk to an AI.
Sovereign AI control is becoming a business continuity issue as autonomous agents take on essential enterprise workflows.
University of Michigan spinout Laplace Intelligence uses AI agents and interactive simulation to stress-test robots and self-driving vehicles before deployment.
What happens to the AI trade when good-enough intelligence does most knowledge work?
Orca Security built Discovery AI, a natural language query agent on Amazon Bedrock that converts plain-English questions into Sonar queries.
Grok 4.7 is now available on Amazon Bedrock.
American Express is introducing a new framework designed to ensure AI agents only make purchases their users have authorized, potentially preventing costly mistakes and disputes as AI-powered shopping grows.
The company’s new releases point to an AI market becoming more personal, with agents and models completing tasks, but enterprises still aren’t ready for this new phase of AI.
Companies in France are deploying agentic computing across industries spanning space, financial services, the public sector and scientific research, demonstrating how the country’s ecosystem has moved from ambition to ap…
Meta Platforms Inc.
Enterprise AI scalability is running into a hard budget wall for some customers.
As enterprises move from debating artificial intelligence adoption to deploying it, AI governance has become the harder question.
If you’ve ever wondered how Claude and similar AI agents can answer complex questions in seconds and where they get the information, you’re not alone.
Sakana AI's MASS method lets one language model improve itself by solving tasks, judging results, and refining workflows, reaching a win rate of nearly 70 percent against the base model after two rounds.
Microsoft researchers found that autonomous AI agents get trapped in what they call "idea basins" because of their growing chat context, local solution regions they can't escape.
When the founders at Phasis Inc.
Outsourcing the essential task of interviewing job applicants to a machine seems lazy at best, negligent at worst.
Andrej Karpathy, co-founder of OpenAI and now at Anthropic, sees a widening knowledge gap in AI.
As agents take on more work for users, companies are deciding whether to let outside AI systems act on their platforms.
arXiv:2610.12822v2 Announce Type: replace Abstract: Multi-agent systems are increasingly used to solve coding tasks by coordinating agents that share code and plans.
arXiv:2610.13098v2 Announce Type: replace Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous supervision from f…
arXiv:2610.13356v2 Announce Type: replace Abstract: Coding agents are increasingly deployed for end-to-end software engineering tasks, where a readily available oracle evaluator that defines the success criteria is often…
arXiv:2610.13438v2 Announce Type: replace Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and tool-use in intera…