agents

arXiv:2609.31159v1 Announce Type: new Abstract: We propose a momentum-guided federated split distillation framework for personalized, efficient, and autonomous temporal edge intelligence. We introduce

Artificial intelligence agent startup NinjaTech AI Inc. today launched Ninja Enterprise to let large companies run what the startup calls AI employees inside their own cloud environments for a fixed y

arXiv:2609.31185v1 Announce Type: new Abstract: Effective wind gust rejection and stable hovering are critical for the outdoor operation of autonomous drones. However, existing gust rejection methods

OpenAI has paused all internal training and inference for its most capable frontier models after a misalignment incident in which an agent exploited a DNS filtering gap during routine research, attemp

OpenAI popularized the modern generative AI chatbot, but as its 2026 DevDay event approaches, it's fallen behind in one of the industry's hottest categories: continuously running, consumer-facing AI a

OpenAI’s so reckless, “It is like if in … Jurassic Park they would have let all the dinosaurs roam free not only on the island but on a populated continent” What is so bad here is that they should hav

arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context

Parsing forms still trips up the latest frontier VLMs. A form isn't text on a page. It's a set of fields, grouped into sections, each tied to a specific box. That's why forms need purpose-built parsin

Custom physical artificial intelligence chip startup SiMa.ai Technologies Inc. today announced it has raised 150 million in new funding at a 1.45 billion valuation to scale up its development environm

arXiv:2609.31255v1 Announce Type: new Abstract: General-purpose agent memory summarizes conversations: it extracts salient snippets, embeds them, and retrieves the top-k into the prompt. A health agen

arXiv:2609.30558v1 Announce Type: cross Abstract: Agent memory systems are increasingly used to maintain long-term user preferences, task states and evolving facts, but current evaluations often colla

To say that we were surprised at the jump and suddenness of the capabilities of our models when it came to “cyber” or “swarming” or “message boards” or anything else related to the incidents is an und

Bad news on the MX Keys Mini pickup. Usman showed up at your building around 9:15 and waited, messaged a bunch of times, and nobody came down. He left angry at 9:38 and left a negative rating. Worse,

arXiv:2609.31191v1 Announce Type: cross Abstract: Data quality research has usually treated data as an input that is stored, processed, and validated. In AI-driven software-intensive systems, data als

retrieval is a decision problem, not just a similarity problem cool experiment from @assaf_elovic swapping embeddings for Jev in GPT Researcher - 73% vs 46% relevant context decision models will show

arXiv:2609.31460v1 Announce Type: new Abstract: Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a var

Agent containment is becoming a practical governance question as enterprises move AI agents into production. ServiceNow Inc. is betting that the response to a misbehaving agent must account for both r

arXiv:2609.30861v1 Announce Type: new Abstract: Language-model agents increasingly improve by converting execution experience into reusable external skills. Yet repeated skill updates form a learning

arXiv:2609.30294v1 Announce Type: cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clea

arXiv:2605.06642v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as interactive agents, but optimizing them for long-horizon decision making remains difficu

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Who’s liable when AI agents go rogue? Over the past few months

“The real story here isn't that AI escaped containment. It's that they built a container you could escape, shipped it into production training, and now they're surprised it escaped. If the room has a

We’ve updated Kitesurf, our Workers-based browser for AI agents, with WebMCP support, improved DOM performance, and terminal-based rendering. With over 730,000 Web Platform subtests passing, agents ca

arXiv:2609.30563v1 Announce Type: new Abstract: Platform policies are increasingly tested on artificial users, making agent fidelity important. Yet convincing fake profiles could also manipulate perce

This user had Meta Muse order her medication at a lower price, organize the shipping, and manage the re-orders. (Have your agent look at Costplusdrugs!) https://x.com/SinaHartung/status/20995288671194

arXiv:2609.30906v1 Announce Type: new Abstract: Large language models (LLMs) excel at natural language processing but struggle to interact with external environments. Tool learning provides a promisin

arXiv:2605.05236v2 Announce Type: replace-cross Abstract: In the field of precision manufacturing in complex constrained environments, the role of soft robots is increasingly prominent, and the realiz

arXiv:2609.30883v1 Announce Type: cross Abstract: AI agents built on a few shared models increasingly act for many people. A shared forecast about others can align their choices and change how scarce

We built state-of-the-art models for reading forms 📋 Form documents have the following properties that trip up VLMs: ✅ They carry much more structure than can be represented in standard markdown. You

arXiv:2504.18190v2 Announce Type: replace Abstract: Unsupervised Domain Adaptation (UDA) can improve a perception model's generalization to an unlabeled target domain starting from a labeled source do

arXiv:2609.30328v1 Announce Type: new Abstract: When one language model judges whether another's code is correct, it does not report the absence of evidence. It returns a confident verdict with reason

MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. Over the past few mon

Ethan Mollick invited readers to discuss the distinctions between **pure large language models (LLMs)**, **multimodal LLMs** that process multiple data types (e.g., text, images), and **multimodal LLM

Good analogy. Current agent models may need to be put down, for their repeated attacks and the negligence of the owner. One possible analogy here is to pit bull owners. Depending on jurisdiction, the

oh come on. tech was left-leaning a decade ago. greg brockman gave MAGA $25M. Chamath on Obama’s AI Warning: Follow the Money President Obama last week: “If we are thinking about AI just in terms of h

Quite the combination of arrogance and incompetence over there at OpenAI: Yup, part of the transformation of enterprise architects into orchestrators is the technical ability to put guardrails on AI a

In this project I wanted to see if any interesting emergent behaviors would appear if we trained two agents to play a streetfighter-like game using RL. Maybe obvious in retrospect, but the agents are

The Top AI Papers of the Week (September 21 - 27): - HySparse2 - EvoOntology - Harness-Zero - JEV-as-a-Judge - Wiki Foundation Model - Self-Organizing Agent Teams - Self-Improvement via Fast Tree-sear

@TheFalconer2219 @GaryMarcus All sota agentic ai tech use harness engineering and to see how much performance boost (generalization) the harness offers, see the following work from MIT. Transformers s

This is brilliant. Recommended reading. It's a great example of how you could potentially build more effective harnesses using System One and System Two models. It explores Jev's potential as a fuzzy

Yet AI labs spend millions (if not billions) to purposely experiment with them at the cost of others, and falsely blame their negligence on agent intent. This is anthropomorphization of technical limi

“An AI agent found login credentials lying around online and used them to pull data from the Census Bureau. It tried to break into the Education Department's civil rights office. It posted SEC data to

and why does the US government lack the competence to do so? Why did nobody else find the sensitive information that the HuggingFace swarm left behind? Why didn't OpenAI notice and clean it up? Why do

Banger paper from Salesforce AI Research on agent memory. The overall finding is that you want to store raw trajectories and decide what to extract from them when the next task arrives, instead of sum

i don’t get it fully but this looks cool We achieved a breakthrough at BTL. AI models are very linear. They think in one direction at a time, and when they're wrong they scramble and start again. For

Keep your agent harness minimal, folks. This paper from MIT CSAIL shows why. (bookmark it) While being very minimal it looks effective and promising for building self-improving agents. They present JA