All entries

Interval-valued SHAP in Tree-Based Models

arXiv:2610.11953v1 Announce Type: new Abstract: Shapley values are among the most popular feature-attribution explanations. Efficient approaches for computing/estimating Shapley values for tree-based

Agents

Intervention anchors and scientific verification in synthetic vascular predictive representations

Content type

All Blog X Post Paper YouTube Reddit GitHub

arXiv:2610.11704v1 Announce Type: new Abstract: Complete orthogonal predictive coordinates do not by themselves bind a latent direction to a named intervention. We present a mathematical and synthetic

agentsarxiv-cs-ai

9 Oct 2026

InterviewPlayground: A Simulation Environment for Evaluating AI Interviewers

arXiv:2610.12023v1 Announce Type: new Abstract: Increasingly, AI interviewers are being developed to elicit open-ended responses in applications like market research, public polling, preference elicit

IntrinSync: Joint Intrinsic Decomposition and Reciprocal Rendering

arXiv:2610.11138v1 Announce Type: new Abstract: Inverse rendering decomposes an image into intrinsic properties such as appearance, illumination, geometry, and material, yet these properties are inher

Industry

Introducing Clef-omni with full multimodality, plus a faster Clef and a cheaper Clef-flash

We are expanding the Clef decision model family with Clef-omni, natively processing audio, video, images, and text in a single pipeline. We’ve also lowered Clef-flash pricing and boosted Clef inferenc

industrycloudflare-ai

Invariant-Measure Reasoners: Stable Representations for Latent Reasoning

arXiv:2610.10996v1 Announce Type: new Abstract: Latent reasoning models repeatedly update a latent state using the same recurrent block. As the recurrent depth increases, the sequence of latent states

IS-Diff: Improving Diffusion-Based Inpainting with Better Initial Seed

arXiv:2509.11638v2 Announce Type: replace Abstract: Diffusion models have shown promising results in free-form inpainting. Recent studies based on refined diffusion samplers or novel architectural des

Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

model-releasesarxiv-cs-cv

arXiv:2610.12310v1 Announce Type: new Abstract: A single multimodal large language model (MLLM) struggles to excel simultaneously at detection, localization, description, and reasoning in multimodal i

Is Memorization Context-Sensitive? Prefix-Based Extraction Beyond Isolated Prefixes

arXiv:2610.12085v1 Announce Type: new Abstract: Large language models (LLMs) can expose memorized training sequences under prefix-based extraction: given a prefix from a training example, the model ma

Is Peer Review Really in Decline? Analyzing Review Quality across Venues and Time

arXiv:2601.15172v2 Announce Type: replace Abstract: Peer review is at the heart of modern science. As submission numbers rise and research communities grow, the decline in review quality is a popular

Applications

Is Real-World Training Data Necessary for Generalist Graph Anomaly Detection?

arXiv:2610.12167v1 Announce Type: new Abstract: Generalist graph anomaly detection (GAD) aims to build a foundation model that detects anomalies on arbitrary unseen graphs without retraining or fine-t

applicationsarxiv-cs-lg

Applications

ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

arXiv:2610.12213v1 Announce Type: cross Abstract: Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Proc

applicationsarxiv-cs-lg

It's Always 10:10: Reference Images Break a Bias That Prompts Only Dent

arXiv:2610.11320v1 Announce Type: new Abstract: Text-to-image models appear to reproduce the habits of the photographs they learned from. Analog clocks are an extreme case: in advertising, watches alm

safetyarxiv-cs-cv

It’s Friday 🎉 Here’s a look at this week’s announcements: — http://SynthID.com is now available globally in English, allowing anyone to use…

model-releasesgoogle-ai--x

It’s Friday 🎉 Here’s a look at this week’s announcements: — http://SynthID.com is now available globally in English, allowing anyone to use our detector portal to easily verify if images, video, or au

Hardware

JEPAs can 𝐧𝐨𝐰 jointly imagine what happens and what to do next! Meet 𝐋𝐞𝐖𝐀𝐌: A JEPA for the real world with 32.3× faster planning, 19…

JEPAs can 𝐧𝐨𝐰 jointly imagine what happens and what to do next! Meet 𝐋𝐞𝐖𝐀𝐌: A JEPA for the real world with 32.3× faster planning, 19 ms per plan Improves success 28.6% → 89.7% on contact-rich manipula

hardwareyann-lecun--x

Industry

Jev developer TypeSafe AI raised ~870M led by a16z at a 7.5B valuation with Sequoia and angel investors also participating; ~33% of the Fortune 500 use Jev (Bloomberg)

Bloomberg: Jev developer TypeSafe AI raised ~870M led by a16z at a 7.5B valuation with Sequoia and angel investors also participating; ~33% of the Fortune 500 use Jev — TypeSafe AI, the startup behind

industrytechmeme

JevForest: Path Voting for Budgeted Feature Acquisition

arXiv:2610.10615v1 Announce Type: cross Abstract: Choosing which information to observe is central to prediction under limited observation budgets. We study JevForest, a feature acquisition policy tha

safetyarxiv-cs-lg

Just another purely open-weight models benchmark

model-releasesr-localllama

Live results, coding benchmarks included, agentic benchmarks included, domains and other classifications filters included. (Spoiler: DeepSeek-V4-Vision-Exp rules, but other models have their rule area

Just Weather Scoring: Efficient End-to-end Nowcasting with Distributional Diffusion

arXiv:2610.12189v1 Announce Type: cross Abstract: Generative diffusion models are well-suited for probabilistic precipitation nowcasting, but existing approaches often rely on separately trained compr

KDFP: A first-principles approach to knowledge distillation in large language models

model-releasesarxiv-cs-lg

arXiv:2610.10854v1 Announce Type: new Abstract: Knowledge distillation is an established technique for improving the capabilities of small, efficient student models by training them with the represent

La-Ribo: RNA Co-Design via Geometry-Latent Flow Matching

arXiv:2610.12236v1 Announce Type: cross Abstract: RNA function arises from the coupling of nucleotide sequence and three-dimensional structure, motivating their joint design. Coordinating global foldi

LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs

model-releasesarxiv-cs-cl

arXiv:2610.11160v1 Announce Type: new Abstract: Lifelong editing of LLMs requires storing thousands of edits after acquisition. A widely used family of approaches attaches one LoRA adapter per edit, w

LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

model-releasesarxiv-cs-lg

arXiv:2610.11538v1 Announce Type: cross Abstract: Deep randomized models fix hidden-layer parameters through random initialization and learn only closed-form readouts, typically adding depth by stacki

Lamarck's Driving School: Discovering Autonomous Driving Training Strategies through Evolutionary Competition

arXiv:2610.11662v1 Announce Type: new Abstract: Autonomous driving capabilities depend strongly on the distribution of scenarios encountered during training. Existing methods commonly construct or dyn

safetyarxiv-cs-ai

Language Modeling is Monotone Compression

arXiv:2610.11031v1 Announce Type: cross Abstract: A long-standing hypothesis in artificial intelligence and neuroscience posits that intelligence is closely related to compression: the ability to comp

Hardware

Language Models as AI Research World Models

arXiv:2610.12235v1 Announce Type: new Abstract: AI research agents automate the cycle of proposing, implementing, and evaluating experiments, opening a path toward recursive self-improvement. Yet thei

hardwarearxiv-cs-cl

Language Models for Page-Level Layout Decisions in E-commerce Search

arXiv:2610.10920v1 Announce Type: cross Abstract: E-commerce search pages are critical touchpoints for millions of online shoppers. While traditional search engines return a ranked list of results, mo

Language-Specific Effects of Tokenizer Choice in Multilingual Language Models

arXiv:2610.12144v1 Announce Type: new Abstract: Tokenizer choice affects multilingual language modeling, but vocabulary capacity is finite and vocabulary size is often constrained: improving represent

Tutorials

Lapras: Latent Reasoning for Time Series Language Models

arXiv:2610.11111v1 Announce Type: new Abstract: Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural lan

tutorialsarxiv-cs-cl

Local Ai

Large Language Model-Assisted Preparation of Transportation Management Plans: A Case Study with WisDOT WisTMP System

arXiv:2610.10650v1 Announce Type: new Abstract: Work zones are critical yet hazardous components of transportation infrastructure, requiring carefully designed Transportation Management Plans (TMPs) t

local-aiarxiv-cs-cl

Large Language Model Turnover Undermines Screening for Artificial Intelligence-Assisted Scientific Writing

model-releasesarxiv-cs-ai

arXiv:2610.11599v1 Announce Type: cross Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this scree

Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged

arXiv:2610.10918v1 Announce Type: new Abstract: Large Language Models (LLMs) are considered to be a more efficient and cost-effective alternative to human judgment for Machine Translation (MT) evaluat

Large-Scale Benchmarking of Quantum Neural Network Configurations for Financial Time Series Forecasting

model-releasesarxiv-cs-lg

arXiv:2610.12148v1 Announce Type: new Abstract: Quantum machine learning, and quantum neural networks (QNNs) in particular, are advancing fields with growing potential. Although systematic comparisons

Last Week in AI #346 - 719 math manuscripts, 2 Western open models, 1 more safety resignation

model-releaseslast-week-in-ai

OpenAI released 719 mathematics manuscripts on October 6, 2026 that were generated by an internal frontier model (not publicly available), covering 372 topic families—including a solution to the Navie

Latent Core Tokenizer: Compress, but Meaningfully

arXiv:2610.12376v1 Announce Type: new Abstract: Tokenizers are commonly optimized for compression, but a compact vocabulary does not necessarily distribute its capacity evenly across languages. We int

Leakage-Controlled Multimodal Learning for Diagnosis and Progression Prediction in Alzheimer's Disease Research

arXiv:2610.10648v1 Announce Type: new Abstract: Alzheimer's disease prediction involves irregular visits, heterogeneous measurements and incomplete modalities. This study presents a multimodal multita

Applications

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

applicationsarxiv-cs-ai

Tutorials

Learning from Hetero Density for Cryo-EM Protein Reconstruction

arXiv:2610.11403v1 Announce Type: new Abstract: Reconstructing protein structures from cryo-electron microscopy (cryo-EM) maps is essential for understanding macromolecular assemblies. Although learni

tutorialsarxiv-cs-lg

Learning from Own Solutions: Self-Conditioned Credit Assignment for Reinforcement Learning with Verifiable Rewards

arXiv:2606.18810v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has driven substantial progress in training LLMs for reasoning tasks, but representative

safetyarxiv-cs-ai

Learning How to Search for Plans with Exponentially Less Space

arXiv:2610.10954v1 Announce Type: new Abstract: Heuristic search for a plan can store exponentially many states, even when its heuristic is almost perfect. We instead learn search control, one specifi

safetyarxiv-cs-ai

Learning infinite context windows in recurrent architectures via spatial neural computing

arXiv:2610.10690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) offer linear-time scaling with sequence length while requiring only constant memory, yet they struggle to capture long-

Local Ai

Learning Kilometer-Scale Weather Prediction with Global-Regional Alignment

arXiv:2610.12401v1 Announce Type: new Abstract: Kilometer-scale regional weather forecasting is essential for local weather warnings and weather-sensitive decisions. Existing data-driven approaches of

local-aiarxiv-cs-lg

Learning Language-Conditioned Traversability Representations for Adaptive Visual Navigation

arXiv:2610.11622v1 Announce Type: new Abstract: Traversability is essential for visual navigation but varies with robot capabilities and user preferences. Conventional pipelines often rely on explicit

researcharxiv-cs-ro

Learning Probabilistic Logic Programs with Functional Gradient Guided Language Models

arXiv:2610.12303v1 Announce Type: new Abstract: Declarative logic programs offer a powerful and interpretable abstraction for encoding relational structure and neurosymbolic reasoning, by expressing d

Learning Projection-Aware 360-Degree Image Rectification via Dual-Projection Fusion

arXiv:2512.00911v2 Announce Type: replace Abstract: Panoramic cameras provide a 360{eg} field of view and are widely used in panoramic vision, immersive visual computing, and robotic perception. Howev

Learning qBIC Resonances across Metasurface Families in Dielectric Fourier Space

arXiv:2610.11500v1 Announce Type: cross Abstract: Bound states in the continuum (BIC) metasurfaces are typically described by geometry-specific parameters, hindering cross-geometry comparison, while u

Learning structured linear dynamical systems from missing observations

arXiv:2610.11869v1 Announce Type: cross Abstract: We consider the problem of learning structured linear dynamical systems over convex sets K, where only a small subset of the observations are availabl

safetyarxiv-cs-lg

Learning the Loop, Not Just the Page: Execution-Grounded Loop Learning for Web Generation

arXiv:2610.11543v1 Announce Type: new Abstract: Functional Web generation is increasingly optimized with executable rewards, yet existing methods largely focus on the quality of the final page and lea

safetyarxiv-cs-cl