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arXiv:2610.19212v1 Announce Type: new Abstract: World models of visual information predict future image frames conditioned on given action sequences. This predicted scene evolution is driven by determ

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Discrete Diffusion Models are Minimax Optimal Under Sparsity

DGX agent

arXiv:2610.19020v1 Announce Type: cross Abstract: Discrete diffusion models have emerged as a leading alternative to autoregressive models for generating text and other categorical data, yet their the

model-releasesarxiv-cs-lg

15 Oct 2026

From Global to Tail Convergence: Dynamics of alpha-Stable Score-Based Generative Models

arXiv:2610.19773v1 Announce Type: new Abstract: Score-based generative models driven by alpha-stable L{evy processes have been proposed as an alternative to Brownian diffusion models, with empirical e

researcharxiv-cs-lg

GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?

arXiv:2610.15129v1 Announce Type: new Abstract: Human social perception is incremental: we infer intent before an utterance is complete, revise our interpretation as new cues arrive, and attend to spe

Toward System One Clinical Intelligence: Parameter-Efficient Fine-Tuning and Counterfactual Explainability of Decision Foundation Models

arXiv:2610.15029v1 Announce Type: cross Abstract: Automated disease classification from patient-reported symptoms requires balancing the speed of lightweight discriminative models against the contextu

UA-Bench: Benchmarking Large Audio-Language Models on Underwater Acoustic Recognition

arXiv:2610.16942v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are fast becoming a general interface to sound, yet how far their broad pretraining carries into specialized domai

Tutorials

MORE: Learning Motion-Oriented Registers for Driving World Models and Planning

arXiv:2610.14871v1 Announce Type: new Abstract: By predicting future states, latent world models provide rich self-supervision for end-to-end driving, but often inherit dense features from pretrained

tutorialsarxiv-cs-cv

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

arXiv:2502.04356v2 Announce Type: replace-cross Abstract: In response to the success of proprietary Large Language Models (LLMs), there is a growing interest in developing open, non-proprietary LLMs a

RAR: Rate-Adaptive Rollout for Time-Consistent Interactive World Models

arXiv:2610.16302v1 Announce Type: new Abstract: Video-based interactive world models aim to enable real-time, user-controllable environments. Yet most existing systems are trained and rolled out at a

Remembering What Matters for Long-Horizon Robotic World Models

arXiv:2610.14583v1 Announce Type: cross Abstract: Autoregressive robot video world models based on discrete visual tokens remain unreliable over long rollout horizons. Retaining the entire generated h

DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models

arXiv:2603.18048v3 Announce Type: replace Abstract: Recent Audio Multimodal Large Language Models (Audio MLLMs) demonstrate impressive performance on speech benchmarks, yet it remains unclear whether

Introducing DigitalOcean Signals and Simulations: see how your agents and models really behave in production, then test the fix before it ships

model-releasesdigitalocean

You ship an agent. It mostly works. Then the feedback loop becomes a support ticket: a user got the wrong answer, a tool call looped four times, a refund went out that shouldn’t have. Standard observa

Meta releases Muse Wonder AI models built to run personal and professional agents

model-releasessiliconangle

Meta Platforms Inc. today released Muse Wonder and Muse Wonder Full, two artificial intelligence models it says are its most capable yet at running agents that handle personal and professional tasks.

SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

Task Context Shapes Component Roles in Language Models

arXiv:2610.13895v1 Announce Type: cross Abstract: Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in eac

LLM-IDEA: Identifiability-Driven Experimental Agent for Autonomous Discovery of Mechanistic World Models

arXiv:2610.11253v1 Announce Type: new Abstract: Large language model agents are being increasingly deployed as autonomous scientists, designing experiments and inferring mechanistic world models with

9 Oct 2026

Phonological Interference in Multilingual Speech Models

arXiv:2610.11275v1 Announce Type: new Abstract: Phoneme-level models transcribe or generate speech as a sequence of phonemes, the smallest sound units that distinguish words. These models enable fine-

local-aiarxiv-cs-cl

9 Oct 2026

jevman: AI decision models play Pac-Man

model-releasesr-localllama

The other week I posted about Jev vs. Kev compared and since then, OpenAI released the decisions endpoint, Cloudflare released Clef and many here asked about Laya as well. This time we compared six po

8 Oct 2026

Training Parallel Speculative Draft Models by Directly Minimizing Expected Decoding Rounds

arXiv:2610.10411v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by using a low-cost draft model to propose tokens that the full-size target model veri

local-aiarxiv-cs-cl

8 Oct 2026

A Systematic Study of Small Language Models on Abstract Reasoning Tasks

model-releasesarxiv-cs-cl

arXiv:2610.08680v1 Announce Type: cross Abstract: Endpoint accuracy on abstract-reasoning benchmarks does not reveal whether a language model has acquired a transferable rule or fit distribution-speci

Have I Seen Enough? Frozen Video-Language Models Encode Evidence Readiness

model-releasesarxiv-cs-cl

arXiv:2610.08560v1 Announce Type: cross Abstract: Streaming video-language models must decide not only what to answer, but whether the evidence needed for the current question has arrived. Existing sy

OTel: Open Telco AI Datasets, Benchmarks, and Models

arXiv:2610.07766v1 Announce Type: new Abstract: We present Open Telco (OTel), an open telecom AI resource that releases derived telecom datasets for retrieval, reranking, instruction tuning, and safet

SoloQ: Calibration-Free Quantization for Diffusion Language Models

arXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based t

Visual Abstention in Unified Multimodal Models

arXiv:2610.07887v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) integrate understanding and generation, yet their generative behavior is rarely governed by what they understand abou

We show how you can use the River API to fine-tune open weight models to beat GPT-6 Astra and Claude Opus 5.5 on tasks you care about, with …

model-releasesclem-delangue--x

We show how you can use the River API to fine-tune open weight models to beat GPT-6 Astra and Claude Opus 5.5 on tasks you care about, with less than 1% of the cost! A few years from now most of the L

A Unified Scaling Law for Time Series Foundation Models

arXiv:2610.05269v1 Announce Type: new Abstract: We develop a Unified Scaling Law and a Unified Theory of Time Series Learning to understand how model capacity and historical information support foreca

InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models

arXiv:2312.01886v4 Announce Type: replace Abstract: Large vision-language models (LVLMs) have demonstrated their incredible capability in visual question answering. However, this rich visual interacti

Localize-and-Detect: Auditing Task-Level Poisoning in Instruction-Tuned Models

arXiv:2610.03960v1 Announce Type: cross Abstract: Instruction fine-tuning adapts a pretrained language model to follow instructions by training it on instruction--response pairs from a collection of t

local-aiarxiv-cs-lg

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

arXiv:2610.04407v1 Announce Type: cross Abstract: Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, tas

local-aiarxiv-cs-lg

Benchmarking Candidate Coverage in Typed Decision Models

arXiv:2610.03387v1 Announce Type: new Abstract: Typed decision models return choices or distributions over answer options supplied at request time. Accuracy with complete options does not establish wh

Evaluating the Retrieval Robustness of Large Language Models

arXiv:2505.21870v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) generally enhances large language models' (LLMs) ability to solve knowledge-intensive tasks. But RAG coul

Reasoning Models Are Accurate but Unsound on Identification

arXiv:2610.03519v1 Announce Type: new Abstract: A reasoning model asked whether a causal effect is recoverable from observational data can fail in two ways: it refuses an identifiable query or answers

Thanks for sharing! We open-sourced code and models. 🤗Huggingface Paper: https://huggingface.co/papers/2609.38597 💻 Code: https://github.c…

model-releasesclem-delangue--x

Thanks for sharing! We open-sourced code and models. 🤗Huggingface Paper: https://huggingface.co/papers/2609.38597 💻 Code: https://github.com/nv-tlabs/PixelUMM 🤗 Model: https://huggingface.co/nvidia/Pi

Tutorials

XGenAct: Geometry-Enhanced World Action Models through Cross-Task Generation

arXiv:2610.03516v1 Announce Type: cross Abstract: World action models (WAMs) have advanced robot control by predicting how observations and actions evolve over time. Despite this progress, RGB and act

tutorialsarxiv-cs-cv

Agents Are Systems, Not Models: Rethinking Agentic Evaluation

arXiv:2610.01618v1 Announce Type: new Abstract: Agent evaluations increasingly go beyond a single success rate, reporting metrics such as cost, consistency, and robustness. Yet they typically treat th

ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

arXiv:2610.01296v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) Diffusion Language Models (DLMs) offer flexible parallel decoding and increased model capacity, but their large number of exper

SALD: Self-Referenced Advantage Learning for Diffusion Models

arXiv:2610.01496v1 Announce Type: new Abstract: Recent work on language-model adaptation has shown that single models can obtain informative training signals by evaluating their behavior in demonstrat

researcharxiv-cs-cv

Stable and Counterfactually Robust Physical World Models from Imposed Structure and Learned Physics

arXiv:2610.00280v1 Announce Type: new Abstract: A world model learns to forecast how a physical system evolves from recorded trajectories, yet the systems it imitates obey physical laws that are neith

From Modes to Memories: Characterizing the Scale-Space Dynamics of Diffusion Models

arXiv:2609.39648v1 Announce Type: cross Abstract: Diffusion models are typically viewed as stochastic processes that transform noise into data. We take a complementary perspective: a diffusion model d

researcharxiv-cs-ai

KlinikeBench: Evaluating Language Models Beyond Diagnostic Accuracy

arXiv:2609.38480v1 Announce Type: cross Abstract: Most clinical benchmarks evaluate language models (LMs) on diagnosis using complete case descriptions. In clinical practice, however, patients present

LOCI: Spatial Linear Memory for Streaming World Models

arXiv:2609.40222v1 Announce Type: new Abstract: When a camera revisits a previously observed region, a video world model should reproduce what was there before. This requires both remembering past obs

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

arXiv:2609.39773v1 Announce Type: new Abstract: Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models a

Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory

arXiv:2606.19998v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed across diverse tasks, yet they remain black boxes whose physical interactions ca

FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models

arXiv:2609.35947v1 Announce Type: new Abstract: Many inference-time tasks for pretrained discrete diffusion models and diffusion language models reduce to drawing samples from a tilted version of the

30 Sept 2026

TagPR: Tag-Guided Process Supervision for Personalization Reasoning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2509.23140v2 Announce Type: replace Abstract: Recent advancements have endowed Large Language Models with impressive general reasoning capabilities. However, these reasoning models often perform

30 Sept 2026

XU-RS: Explaining Credal Width in Random-Set Language Models

arXiv:2609.37594v1 Announce Type: new Abstract: Uncertainty estimates tell us how unsure a model is, but not why. Without knowing which parts of an input influences a model's uncertainty, we cannot te

30 Sept 2026

Causally Debiased Latent Action Model for Embodied Action-Conditioned World Models

arXiv:2607.09185v2 Announce Type: replace Abstract: Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions. However, learning controllable ACWMs re

researcharxiv-cs-cv

29 Sept 2026

Constella Preview: Swap Query Models Without Re-Embedding