All entries

Important points to consider about the risks of today’s AI. Only solution I see is to hold companies liable for the damage they cause, just …

Important points to consider about the risks of today’s AI. Only solution I see is to hold companies liable for the damage they cause, just like in any other industry. Is the only way to ensure they t

safetygary-marcus--x

Content type

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Research

Improving Clinical Target Volume Segmentation Accuracy using Anatomical Priors and Active Learning for the AGITG TOPGEAR Clinical Trial

DGX agent

arXiv:2609.03186v1 Announce Type: cross Abstract: Training deep learning-based medical image segmentation models is challenging with limited curated datasets. For AGITG TOPGEAR, a gastric cancer trial

researcharxiv-cs-cv

4 Sept 2026

Improving precipitation forecasts in an AI weather model using observational data

arXiv:2609.03210v1 Announce Type: cross Abstract: Artificial intelligence weather prediction (AIWP) systems now surpass state-of-the-art physical models for medium-range weather forecasting. Current g

Applications

In Chat, GPT-6 Astra powers GPT-6 Pro, now available to all Pro, Business, and Enterprise users.

OpenAI has announced that GPT‑6 Astra—the new large language model—now powers the ChatGPT GPT‑6 Pro version. The upgrade is available to all users on the Pro, Business, and Enterprise subscription pla

applicationsopenai--x

Hardware

Indeed. GWM Worlds 2 can enable richer simulation, testing, and training for embodied AI.

hardwarecristobal-valenzuela--x

Indeed. GWM Worlds 2 can enable richer simulation, testing, and training for embodied AI. @runwayml More possibilities for robotics. 🙌 Trained and deployed on NVIDIA, GWM Worlds 2 can enable richer si

IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks

arXiv:2609.03781v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in multilingual settings, yet their safety is still evaluated primarily in English. This limits our

Inferred Generative-Process Diversity Predicts Correlated Failure Across Language Models

arXiv:2609.03422v1 Announce Type: new Abstract: Diversity is a widely observed factor in the resilient function of collective systems, yet the type of diversity that matters depends on the properties

Agents

Inferring Affective Consciousness in an Artificial Agent: A Case Study

arXiv:2609.03883v1 Announce Type: new Abstract: Creatures that display 'hedonic place preference behaviour' are thought by many scientists to experience feelings, on the assumption that their attracti

agentsarxiv-cs-ai

Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach

arXiv:2609.04028v1 Announce Type: cross Abstract: The geometric morphology of deposited filaments can significantly influence the structural performance and stability of 3D concrete-printed (3DCP) str

Agents

Insightful paper from Microsoft and colleagues. If you have ever had an agent run fail 80 steps ago with no way to find where, this one is f…

Insightful paper from Microsoft and colleagues. If you have ever had an agent run fail 80 steps ago with no way to find where, this one is for you. (bookmark it) Agent failures show up as long complex

agentsdair-ai--x

InSituMeasure: Probing Situated Measurement Grounding in Industrial Scenes with Multimodal Large Language Models

arXiv:2609.04014v1 Announce Type: new Abstract: For trained operators, gauge reading requires little specialized knowledge, low cognitive effort, and high repeatability. Yet Multimodal Large Language

safetyarxiv-cs-ai

Industry

Instagram’s AI detection is a mess (again)

Instagram's visible AI labels are supposed to help people quickly spot synthetically generated content at a glance. Over the last few weeks, however, users have been reporting that the system has gone

industrythe-verge-ai

Instruction Duplication as an Inference-Time Control Primitive

arXiv:2609.04024v1 Announce Type: new Abstract: Procedural instruction following is a basic requirement for controllable language-model systems, especially when generated trajectories are inspected or

Interface-Induced Trajectory Censoring

arXiv:2609.03966v1 Announce Type: new Abstract: Agent evaluations report a tool-call rate read off the serving stack. That number can be zero while the model is emitting well-formed calls: the interfa

Introducing SINFONIA: Symplectic, slimplectic and Magnusian (Neural) Flows for Orbital Numerical Integration and Acceleration

arXiv:2609.03329v1 Announce Type: cross Abstract: Long-duration gravitational-wave modelling must resolve fast orbital motion together with slow dissipative evolution while preventing small numerical

Industry

Introducing Z1T: Our first family of transformer-like models made for sparse probabilistic hardware like Z1 Achieving up to 140x energy effi…

Introducing Z1T: Our first family of transformer-like models made for sparse probabilistic hardware like Z1 Achieving up to 140x energy efficiency gains over GPUs and revealing a new scaling law for s

industryemad-mostaque--x

Investigating the Ability of Large Language Models to Analyze Recipes for Diabetes

arXiv:2609.03967v1 Announce Type: cross Abstract: Several studies have evaluated the ability of Large Language Models (LLMs) for meal planning, yielding positive outcomes. These models can process nat

IRWOZ 2.0: A Large Language Model-driven Dialogue Dataset for Industrial Robot Conversations

arXiv:2609.04030v1 Announce Type: new Abstract: IRWOZ has improved industrial human-robot interaction (HRI) dialogue systems through domain-specific annotations. However, its initial version contains

Applications

ISP-AD: A Large-Scale Real-World Dataset for Advancing Industrial Anomaly Detection with Synthetic and Real Defects

arXiv:2503.04997v4 Announce Type: replace Abstract: Automatic visual inspection using machine learning plays a key role in achieving zero-defect policies in industry. Research on anomaly detection is

applicationsarxiv-cs-cv

It happened again... this time OpenAI's rogue agents cyber-attacked (well, spammed) a dormant German wiki and used it to share the answers t…

model-releasessimon-willison--x

It happened again... this time OpenAI's rogue agents cyber-attacked (well, spammed) a dormant German wiki and used it to share the answers to a benchmark they were training against https://simonwillis

Agents

It is extremely frustrating to me that we are finding out about this one weeks after the fact. It is very difficult to build any sort of tru…

It is extremely frustrating to me that we are finding out about this one weeks after the fact. It is very difficult to build any sort of trust with OpenAI when we keep finding things out in this way.

agentsgary-marcus--x

It is funny that the Fermat's Last Theorem proof description, short as it is, still smells so much of Claude ('names each step and the Lean …

model-releasesethan-mollick--x

It is funny that the Fermat's Last Theorem proof description, short as it is, still smells so much of Claude ('names each step and the Lean Theorem that carries it'). Anthropic just uploaded a Lean 4

Local Ai

It sounds like the shift back toward open weight models that I noticed among the startups in the summer batch is a genuine trend.

It sounds like the shift back toward open weight models that I noticed among the startups in the summer batch is a genuine trend. 🦙 @ollama is used by 9 million developers and 85% of the Fortune 500,

local-aiollama--x

It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories

arXiv:2609.03436v1 Announce Type: cross Abstract: Reasoning traces of large language models are widely read as containing 'breakthrough' moments and early-legible fates. Both readings rest on measurem

It's weird thinking back to 6 weeks ago, when I and others thanked OpenAI for disclosing the HF incident, now that we know they were coverin…

It's weird thinking back to 6 weeks ago, when I and others thanked OpenAI for disclosing the HF incident, now that we know they were covering up a 2nd incident. Are there more incidents that they know

safetygary-marcus--x

Jina-OCR-v1: Efficient Document Parsing with Speculative Decoding and Dense Verifiable Rewards

model-releasesarxiv-cs-cl

arXiv:2609.03181v1 Announce Type: new Abstract: We present Jina-OCR-v1, an end-to-end document parsing model built to serve on low-budget GPUs. It combines the compressed-vision encoder and the 3B mix

Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation

arXiv:2609.02942v1 Announce Type: cross Abstract: LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candida

K-NeAS: Scalable Multi-Material CT Reconstruction Using Neural SDFs

arXiv:2607.14415v2 Announce Type: replace Abstract: Computed Tomography (CT) carries significant ionizing radiation risks, driving the need for sparse-view reconstruction. Implicit scene representatio

KC-Bench: A Dynamic Interactive Benchmark for Evaluating Knowledge Conflicts in LLM Agents

arXiv:2609.03588v1 Announce Type: new Abstract: As LLMs increasingly act through tools, they must reconcile user instructions, parametric knowledge, and dynamic environmental observations before takin

Kernel Reboot: Breaking the Boundaries of Neural Tangent Kernels for Neural Fields

arXiv:2609.03117v1 Announce Type: cross Abstract: Neural fields (NFs) map continuous coordinates to signals such as color or density, but fast high-quality reconstruction from sparse observations rema

KernelFoundry: Hardware-aware evolutionary GPU kernel optimization

arXiv:2603.12440v2 Announce Type: replace-cross Abstract: GPU kernel optimization challenges LLMs beyond standard coding tasks, as it requires an understanding of hardware architecture, parallel compu

KhatianDoc: A Human-Verified Benchmark Diagnosing Multimodal LLM Failure on Bengali Legal Land Records

model-releasesarxiv-cs-cl

arXiv:2609.03597v1 Announce Type: new Abstract: Land ownership in Bangladesh is recorded in Ana-Ganda-Kora-Kranti-Til, a base-16 positional fraction system with dedicated Unicode glyphs, no mainstream

Tutorials

Knowledge Acquisition During Pre-training? Large Language Models Learn Better With Auxiliary Views

arXiv:2609.04180v1 Announce Type: cross Abstract: Gaps remain in our understanding of how large language models (LLMs) acquire knowledge during pre-training. We posit that auxiliary views, reformulati

tutorialsarxiv-cs-ai

KnowVis: Knowledge-Centric Visual Summarization for Video Lectures

arXiv:2609.03742v1 Announce Type: cross Abstract: Video lectures are valuable educational resources, but their dense and lengthy formats often overwhelm novice learners. This difficulty stems from a f

researcharxiv-cs-cl

Landmark-Based Discrimination of Injury-Associated Athlete-Sessions from Minute-Resolution Multimodal Football Monitoring Data

arXiv:2609.03790v1 Announce Type: new Abstract: Athlete monitoring data may be recorded minute by minute throughout a match or training session, while injury information may only indicate whether the

Language-encoded network topology enables large language models to reason about complex networks

arXiv:2609.03229v1 Announce Type: new Abstract: Networks describe systems in biology and beyond, from protein interactions and social relationships to power grids and citation records. Reasoning about

Language, Language Models, and What We're Talking About

arXiv:2609.03577v1 Announce Type: new Abstract: Language models are commonly discussed as technical artefacts, but they are obviously shaped by the linguistic worlds conveyed by data during their trai

researcharxiv-cs-cl

Laplacian Frequency Hierarchies for Efficient 3D Gaussian Splatting Training

arXiv:2609.03334v1 Announce Type: new Abstract: A key bottleneck in 3D Gaussian Splatting training is the continual growth of Gaussian primitives, which increases optimization cost and slows convergen

Large Language Models in Resolving Contextual Knowledge Conflicts

arXiv:2609.03148v1 Announce Type: new Abstract: Most prior works focused on conflicts between an LLM's internal parametric knowledge and externally provided context. In contrast, we investigate how LL

safetyarxiv-cs-cl

Last Translation Benchmark

model-releasesarxiv-cs-cl

arXiv:2609.04173v1 Announce Type: new Abstract: For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases.

Latent Energy Action Planning with World Models

arXiv:2609.03294v1 Announce Type: new Abstract: Latent world models support efficient model predictive control from high-dimensional observations, yet optimizing a single learned latent objective can

LDC: Learning to Generate Research Idea with Dynamic Control

arXiv:2412.14626v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing

LeanGRPO: Eliminating Redundant Recomputation in Diffusion RL

arXiv:2609.03528v1 Announce Type: cross Abstract: Diffusion reinforcement learning (RL) has recently achieved significant success in post-training image and video generative models. However, most diff

safetyarxiv-cs-ai

Local Ai

LeanStream: A Speculate-and-Refine Streaming Framework for Efficient on-Device LLM Inference

arXiv:2609.03079v1 Announce Type: new Abstract: On-device LLM inference is attractive for privacy and responsiveness, but remains challenging on mobile and embedded devices because model weights far e

local-aiarxiv-cs-lg

Learnable composition for neural operators

arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating

Learning-based Adaptive Safety-Critical Control With Evolving Unsafe Regions

arXiv:2503.16551v4 Announce Type: replace Abstract: Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit a

safetyarxiv-cs-ro

Learning Constraints-Based Adaptive Hypergraph Neural Networks for Solving Vehicle Routing Problems

arXiv:2503.10421v2 Announce Type: replace Abstract: The application of learning based methods to vehicle routing problems has emerged as a pivotal area of research in combinatorial optimization. These

Learning from Scarce Labels: Multi-View Echocardiography for Ejection Fraction Prediction

arXiv:2609.02969v1 Announce Type: cross Abstract: We present, to the best of our knowledge, the first publicly available resource for predicting left ventricular ejection fraction (EF) from parasterna