2026-09-03

蚂蚁集团推出统一宽表系统OmniTable，论文获评VLDB 2026工业赛道最佳论文

LLM judges are widely used to evaluate agentic tool-calling systems, yet their reliability on structured, dependency-driven workflows remains largely unexamined. We present AgentJudgeBench, the first benchmark to systematically study LLM-as-a-judge reliability for agentic tool-calling over workflow DAGs, as distinct from the broader LLM-as-a-judge task of open-ended text or preference evaluation. The benchmark comprises 3,808 instances spanning six DAG topologies and three difficulty tiers, eval

一张图补全3D世界，还能给机器人造训练场

Claude’s most advanced models for coding and knowledge work Discussion | Link

Article URL: Comments URL: Points: 68 # Comments: 48

The US government wrote a letter in support of OpenAI’s argument that training AI on others' intellectual property is fair use.

We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as large video generators become more capable, language is emerging as a natural interface for control. MiniMax-H3, for example, already supports zero-shot control of character behavior and camera motion through natural-language instructions. Building on this, H3-World turns this coarse language interface into precise, temporally grounded world contr

An identity theft search site claimed to have more than 150 million driver's license photos stolen from an ID verification service. The crime site has now shut down.

Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectories are expensive to collect and inherently limited in diversity. Egocentric videos offer a far more scalable source of embodied experience, capturing object interactions, contact dynamics, tool use, and long-horizon behaviors across diverse environments. The central challenge is how to convert this abundant but action-free experience into effecti

A central bottleneck in multi-hop Question Answering (QA) is that the granularity at which a question is expressed often differs from the granularity at which corpus evidence is retrievable. Existing methods address this mismatch by imposing fixed graph structures over the corpus, by iteratively reformulating the query, or by executing a generated program over it, but these strategies do not explicitly decide when a query unit is already supported by evidence and when it should be refined. We fo

While unified multimodal models (UMMs) jointly perform visual understanding and generation within a single model, functional unification does not guarantee learning synergy: the two objectives may reinforce each other, compete for capacity, or merely coexist. We investigate their relationship at the representation, task, and system levels in a controlled, structurally native setting without pretrained vision priors. At the representation level, we find that each objective provides useful signal

Long-horizon complex tasks require foundation models to accumulate information, maintain internal states, and adapt over extended interactions. Safety should be an intrinsic property of the model itself, rather than a behavioral constraint relying solely on external safeguards or post-hoc alignment such as supervised fine-tuning. This motivates Safety from Within, where safety-relevant capabilities are represented and invoked through the model's native computation. We present Safin-1, a family o

> "Qwen 3.8 is a damn good coder, but a terrible collaborator" It modifies SO many things in my scripts for what should be a 2 line PR, I get a 100 line linter style mess that looks like a high school freshmen got his hands on vs code and pushed code in. It can't maintain a common style, if I give it a script with a certain naming and layout, 3.6 one shots small changes that fit into my structure. 3.8 will add code that looks much more advanced, handling, strict type checks . But if it's just my

无论你此前让Claude处理什么任务，Fable 5.1都能做更多，并且把最难的部分完成得更出色

Self-play is an effective paradigm for language-model self-evolution, but without guidance, solver performance can plateau or decline across rounds. Unguided methods steer question generation with signals such as difficulty, learnability, or diversity. These signals keep questions challenging and varied but do not specify which unresolved reasoning weaknesses later rounds should target. Guided methods obtain direction from external task resources, including human examples, document corpora, or s

Interactive world models extend video generation from offline clip synthesis toward persistent simulation of interactive virtual worlds, enabling applications in games, robotics, embodied agents, and XR. Achieving stable long-horizon interactive generation, however, remains challenging, as the model must simultaneously preserve scene geometry, dynamic consistency, and camera control while supporting real-time autoregressive generation. Building upon Matrix-Game 3.0, we present Matrix-Game 3.5, a

Chain-of-thought (CoT) monitoring assumes that reasoning traces faithfully record the information that shapes a model's answer. Existing faithfulness tests often place explicit bias cues in the user message, while agents may encounter preferences through tool returns or raw artifacts. We introduce FACE-Eval (Faithful Attribution of Cue Effects Evaluation), a 5,100-sample evaluation that varies cue location (user message or tool return) and explicitness (direct summary or raw artifact). We measur

Release: datasette-mcp 0.2 "rows" from execute_sql is now an array of objects. Previously it was an array of arrays. This should help weaker models avoid losing track of which positional array element maps to which column. #1 Now depends on mcp>=2.1.1 . This is the first non-alpha release of the plugin. I'm confident it's ready as I've been using it quite a bit myself. Tags: datasette , model-context-protocol

Just uploaded the full 5.94 billion TikTok video dataset to Hugging Face. It’s fully open source: This dataset was collected using a TikTok mobile app reverse-engineering method I developed a few years ago. The method allowed me to extract billions of videos, profiles, comments and replies, hashtags, sounds, and more. Full write-up and code here: Disclaimer: The TikTok app exposes 24 endpoints that can be accessed without a TikTok account, so the data itself is publicly accessible. But accessing

I wrote some notes on what's new in the (published) Fable 5.1 system prompt in comparison to Fable 5 - it's mostly about not reproducing song lyrics and avoiding drawing copyrighted characters simonwillison.net/2026/Sep/2/c...

The acquisition also leaves Sequoia-backed Serval as the de facto startup leader in AI IT service automation, industry watchers believe.

Google's Pro model updates are seemingly paused, but there's yet another Gemini Flash today.

In another case of it being quicker to build a tool than hunt around to find something that does what you need, here's a little vibe-coded thing for turning one or more GeoJSON shapes into a rendered PNG simonwillison.net/2026/Sep/1/g...

saw the post the other day where people said Minecraft clones aren't impressive anymore, because at this point the whole thing might as well be in the training data. so i tried something slightly different, which is asking a local model to write a mod for the real game, using the Fabric API the model is GLM 5.3 Flash (Q4 quant, running on a rented 4x RTX PRO 6000 box). this wasn't done in prompt or a loop, i would ask for changes, then review them and i kept going like that until i was happy wit

Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodiments. Modern vision-language models (VLMs) already encode spatial priors for visual grounding, spatial reasoning, and pointing, but these capabilities are rarely elicited directly for robot control. Existing navigation systems instead rely on task- or embodiment-specific components, fragmenting perception, reasoning, and action while offering limi

Multimodal Large Language Models (MLLMs) are strong perceivers of images and video. We ask how far that reach extends into acting: dropping an MLLM directly into a drone's control loop, with its entire action space declared solely in the prompt. Recent systems approach this setting but increasingly narrow the model's decision-making. We widen it back. We introduce DroneCATS-Agent, an architecture where the MLLM is a swappable component, and DroneCATS, a benchmark treating the model as the indepe

arXiv:2609.00002v1 Announce Type: new Abstract: World models enable language-model agents to predict environment dynamics and plan before acting. In text environments, the model must learn symbolic action effects from serialized state descriptions, but the role of serialization structure remains underexplored. We present HyperWorld, a controlled study of state serialization for learned textual world models. We compare raw observations with three symbolic serializations of the same ground-truth s

Hi there my dear people of r/selfhosted ! Fresh bunch of Dawarich news is due, make yourself comfortable :) To whom it may concern, Dawarich — is your (is and always will be) a free open source self-hostable alternative to Google Timeline. --- Our links: Github: Website: iOS app: Android app: --- Nine releases, what a month! And not a puny ones, this time we managed to speedrocket Dawarich performance in browser. If you have hundreds of thousands (or even millions!) of points and you'd love to s

One GPU drops off immediately when vllm is started and the other throws CUDA errors on start

Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling agents to reason and act in interactive environments. Existing frameworks largely cast these agents as systems for solving user-specified, bounded tasks. An increasingly important goal is for language agents to provide persistent assistance in long-lived settings where user needs, context, and service procedures persist and change, and to remain u

I am still waiting for Llama 5, because Muse Spark will be too big for me, or just something between Glimmer and Spark

A startup called Mostik has a wild new approach to combining the capabilities of AI models.

NYC public schools are taking a year without generative AI tools.

Fervo's deal with Google could expand to 1 gigawatt of geothermal power, enough to supply a very large AI data center in Utah.

arXiv:2609.00137v1 Announce Type: new Abstract: AI is increasingly used in the R\&D process that produces future AI systems. We study the conditions under which this feedback becomes self-amplifying. Our model describes how the rate of AI capability growth depends on baseline research productivity, recursive feedback, and the increasing difficulty of research progress. We derive a recursive reproduction number, $\mathcal{R}_{\mathrm{AI}}$, that determines whether improvements are amplified or da

I like AI and use it daily so AI by itself isn't a problem. But I feel like some colleagues use it in a weird/wrong way. I have this one colleague who uses AI to its maximum capability, he is a frontend dev who writes the frontend to an application my team is building. Its all done by AI, and I don't really care. He can do it in whatever way he want's. My problem with his AI usage is that he often makes requests through slack to my team. Either a bug or a feature request. But instead of writing

arXiv:2609.00003v1 Announce Type: new Abstract: Machine unlearning studies the removal of knowledge from an AI model, making the system forget a concept it previously learned. Despite rapid progress in generative machine unlearning, the unintended degradation of semantically related concepts that should have been retained (henceforth, interference) remains poorly characterized and inconsistently evaluated. This paper introduces I-CARE, a methodology that formalizes interference as a first-class

arXiv:2609.00018v1 Announce Type: new Abstract: Computer science papers rely heavily on diagrams: architecture drawings, system flowcharts, and pipeline schematics that often carry more information than the text around them. There is currently no public dataset that pairs this specific kind of figure with captions, context, questions, answers, and step-by-step reasoning, which is exactly what is needed to train a vision-language model to understand them. We present \textbf{SCAFFOLD}\footnote{ a

Main thread is here: Muse Spark 1.3 - - Sept 2026 (197 comments)

Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, summaries, or graph facts as isolated fragments. Although searchable, such fragments are not generation-ready: language models must reconstruct cross-modal and temporal alignments at inference time, when context is limited and attribution is difficult. We propose EM^2Mem, an event-centric multimodal memory framework that binds heterogeneous evidence