All entries

vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

arXiv:2610.05095v1 Announce Type: cross Abstract: Latent Dirichlet Allocation (LDA) and models derived from it remain widely used topic models. LDA observes each document as a bag-of-words and models

Content type

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VolS-GS: Relightable Gaussian Splatting with Volumetric Subsurface Scattering

DGX agent

arXiv:2610.04007v1 Announce Type: new Abstract: We present VolS-GS, a relightable Gaussian splatting framework that reconstructs objects from one-light-at-a-time (OLAT) captures and renders them under

researcharxiv-cs-cv

6 Oct 2026

Voltic: Distinguishing Volatility from Stochasticity in Recurrent Memory

arXiv:2610.05700v1 Announce Type: new Abstract: Recurrent sequence models must decide how strongly to overwrite their memory at each token. Read as Bayesian filtering, this write is the gain of a Kalm

Hardware

WAMJET: A Harness for World Action Model Acceleration

arXiv:2610.03797v1 Announce Type: new Abstract: World Action Models (WAMs) leverage pretrained video foundation models for robot manipulation, but their large backbones and video-action co-prediction

hardwarearxiv-cs-cv

WASP: Weakly Aligned Spatiotemporal Pairs for Fetal Brain MRI-Ultrasound Learning

arXiv:2610.04601v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) is widely regarded as the optimal sensor for fetal brain analysis due to its superior soft-tissue contrast and anatomic

safetyarxiv-cs-cv

WasserMan: Benchmark for Underwater Manipulation Policy Learning

model-releasesarxiv-cs-ro

arXiv:2610.04536v1 Announce Type: new Abstract: Underwater manipulation couples visual decisions, contact forces and a thruster-controlled floating base. We introduce WasserMan, to our knowledge the f

Watermarking: from Impossibility to Auditable Compliance

arXiv:2610.06317v1 Announce Type: cross Abstract: Article 50 (2) of the EU Artificial Intelligence Act requires providers of generative systems to make synthetic outputs machine-readable and detectabl

safetyarxiv-cs-lg

Watermarks and Fingerprints as Soft Bindings for Content Provenance: An Open-Licence Benchmark for Images, Audio and Video

arXiv:2610.04151v1 Announce Type: new Abstract: Content-provenance standards such as C2PA let a platform recover a stripped manifest through a soft binding: an invisible watermark read from the conten

WaveGSSM: Graph Wave State Space Models for Propagating Spatio-Temporal Patterns

arXiv:2610.06540v1 Announce Type: new Abstract: Spatio-temporal graph models typically encode each snapshot with a GNN and then connect the resulting representations through a temporal module. This sp

We analyzed a year of agent research across 4 tasks: deep research, RAG indexing, agentic search and coding. Found that first asking ‘Is thi…

We analyzed a year of agent research across 4 tasks: deep research, RAG indexing, agentic search and coding. Found that first asking ‘Is this task verifiable?’ exposed inefficiencies in the agent arch

agentsai21-labs--x

We are releasing the only Western OSS LLM that is competitive with the best Chinese OSS models for coding tasks! Mistral Large 4 preview, AK…

model-releasesarthur-mensch--x

We are releasing the only Western OSS LLM that is competitive with the best Chinese OSS models for coding tasks! Mistral Large 4 preview, AKA le Chonk 🐈 is SOTA OSS on cyber and human evals. Check 🧵 b

We just raised $7.7M to kill every subscription for agents. Introducing http://monid.ai, the openrouter for agent tools. Your agents can now…

We just raised $7.7M to kill every subscription for agents. Introducing http://monid.ai, the openrouter for agent tools. Your agents can now: > discover, run, and pay for tools at runtime > use 2,500

agentsyohei-nakajima--x

Weave Mamba Fusion: Global Cross-Scale Interaction for Lightweight Face Detection

arXiv:2610.05865v1 Announce Type: new Abstract: Feature pyramid methods, from FPN to BiFPN, have achieved strong performance in face detection by fusing multi-scale features. However, detecting faces

Weight Decay and Neuron Condensation: A Three-Stage Analysis of Two-Layer ReLU Networks

arXiv:2610.04533v1 Announce Type: new Abstract: Weight decay is widely used as a regularization technique in neural network training, yet its role in neuron condensation (parameter direction alignment

We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent…

We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence a

model-releasesopenai--x

We’re so back.

model-releaseslm-studio--x

We’re so back. Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on

We’re using GLM-5.3 Flash instead of frontier models on a massive production codebase

At my company, we’re using GLM-5.3 Flash internally for software engineering work, and I’ve been genuinely impressed by it. I work in a very large production environment with projects totaling **milli

agentsr-localllama

What agent traces can tell you without an LLM judge

Some agent failures are already in the trace. tracelint proves them on Phoenix OpenInference spans and fails CI, without an LLM judge. The post What agent traces can tell you without an LLM judge appe

agentsarize-ai

What Do Verifiable Rewards Teach Video-Language Models About Time? A Controlled Multi-Model Study

arXiv:2610.03792v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has produced large reasoning gains in language models, and verifiable video benchmarks make it app

What Does a Harness Buy? Tokens, Mostly

arXiv:2610.04433v1 Announce Type: cross Abstract: A coding agent is a language model wrapped in a harness: the system prompt, the tool set, and the context management that turn a chat model into somet

What Does a Harness Repair? A Preregistered Study of Visibility, Baseline Adequacy and Evaluation Defects

arXiv:2610.05533v1 Announce Type: new Abstract: Harness search keeps a change to the prompts, reasoning switches, token budgets or parsers around a frozen model if the change raises a score. Such a ga

What Does an Observability Foundation Model Know?

arXiv:2610.05577v1 Announce Type: new Abstract: A linear probe can show that a label is recoverable from a model's hidden states, but not whether that goes beyond what the input already reveals, or wh

What Does It Cost to Simulate a Quantum Sentence Classifier? An Energy and Compute Perspective on Near-Term QNLP

arXiv:2610.06176v1 Announce Type: cross Abstract: Near-term quantum natural language processing (QNLP) experiments often run on classical simulators, so simulator cost is part of the field's practical

What Gradients Add to Text Leakage in Split Language Models, Counted per Token and per Document

arXiv:2610.04128v1 Announce Type: cross Abstract: Split learning lets a client train a language model on a server without sending its text. The client runs the first layers itself and sends the server

Tutorials

What Matters for Latent Reasoning with Flow Matching

arXiv:2610.06666v1 Announce Type: new Abstract: Latent reasoning lets a large language model (LLM) think in a continuous space and verbalize only the answer. We argue that an effective latent thought

tutorialsarxiv-cs-lg

What May an Agent Change About Itself? A Containment Floor for Self-Configuring Agent Runtimes

arXiv:2610.06274v1 Announce Type: new Abstract: Many agent runtimes give the agent a tool for editing its own configuration. Some of that configuration grants abilities, such as enabling a tool. Other

agentsarxiv-cs-lg

What the Guard Misses, the Robot Executes: Implied Harm in VLA Instructions

arXiv:2610.05818v1 Announce Type: new Abstract: Vision-language-action models (VLAs) act on instructions without being able to refuse, so screening harmful requests falls to monitors. We test whether

researcharxiv-cs-ro

What to Preserve in Recursive Computation: A Local Predictive Sufficiency Principle

arXiv:2610.04303v1 Announce Type: new Abstract: Recursive computation repeatedly compresses or reuses intermediate states, creating a simple tension: information that must remain useful across longer

What Will Post-Training Fix? Per-Problem Gains Are Shared Across Independent RL Runs, and Existing Checkpoints Predict Them Better Than A Priori Signals

arXiv:2610.04978v1 Announce Type: new Abstract: Data selection, curricula and the evaluation of post-training recipes all assume that we can tell, before training, which problems a model will improve

Applications

When and What to Prune? Stage-Aware Visual Token Pruning for Efficient VLA

arXiv:2610.05273v1 Announce Type: new Abstract: Visual token pruning is an effective way to accelerate vision-language models and is especially useful for vision-language-action (VLA) inference, where

applicationsarxiv-cs-cv

When Are Concept Bottleneck Model Explanations Faithful and Compact?

arXiv:2610.06285v1 Announce Type: new Abstract: Concept bottleneck models (CBMs) are neural classifiers that allow to explain their decisions via high-level concepts, potentially enabling understandin

Tutorials

When Can Voting Help, Hurt, or Change Course? Exact Structure of Binary Test-Time Aggregation

arXiv:2605.05592v2 Announce Type: replace Abstract: Increasing a voting budget can improve or reduce population accuracy, and an initial gain or loss need not persist. We give a complete structural cl

tutorialsarxiv-cs-lg

When Debate Helps: Proposal Supply and Verification-Aware Readout in Multi-Agent Reasoning

arXiv:2610.04686v1 Announce Type: cross Abstract: Multi-agent debate can improve reasoning, yet often fails to beat simple majority voting. We argue that successful debate requires two distinct mechan

agentsarxiv-cs-lg

Tutorials

When Does a Diffusion Model Decide What to Draw ?

arXiv:2610.05645v1 Announce Type: new Abstract: A diffusion model starts from pure noise and removes it step by step. Somewhere along the way it stops being able to become 'anything' and becomes commi

tutorialsarxiv-cs-lg

When Does Longer Reasoning Help? Predicting Mathematical Reasoning Through Discovery and Execution

arXiv:2610.05322v1 Announce Type: new Abstract: Test-time compute can improve mathematical reasoning, but can short-budget runs predict how mathematical reasoning scales with additional compute? We in

When Does Retrieval Help? A Study of In-Context Adaptation in Vision-Language-Action Models

arXiv:2610.05492v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong potential as generalist robot policies, but adapting them to unseen tasks often requires costly pa

When Is Enough Enough in Self-Evolving LLM Systems?

arXiv:2610.04756v1 Announce Type: cross Abstract: Self-evolving large language model (LLM) systems repeatedly propose, evaluate, and incorporate updates to prompts, skills, or other persistent artifac

When Low Prediction Error Misleads Planning: Diagnosing Representation, Dynamics, and Decision Failures in Latent World Models

arXiv:2610.05550v1 Announce Type: new Abstract: The component that dominates a latent world model's prediction error need not be the one whose repair most improves action selection. We show this by co

When the Cross-Silo Federation Goes Offline: Continual Learning for Site Onboarding with Limited Unlabeled Data

arXiv:2610.05598v1 Announce Type: new Abstract: An organization often holds too little labeled data to train a model that generalizes, and the records that would supply the rest sit with organizations

agentsarxiv-cs-lg

When the noncommutative AM-GM inequality holds

arXiv:2610.04874v1 Announce Type: cross Abstract: In this note, we prove that the noncommutative AM-GM inequality holds if nge 2lceil m/2 rceil^2. The motivation comes from counterexamples constructed

When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models

arXiv:2610.05719v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models serve as unified policies for robotic manipulation, yet their expensive inference forces robots to pause between pol

safetyarxiv-cs-ro

Where Does Jagged Competence Come From?

arXiv:2610.03831v1 Announce Type: new Abstract: Capable systems often show jagged competence: low average error alongside failures on particular inputs. We ask where it comes from in a task built from

Where Does the Semantic Gain Come From? A Reproduction and Extension of Semantic Knowledge-driven Contrastive Learning for Long-Tailed Recognition

arXiv:2610.04104v1 Announce Type: new Abstract: Semantic Knowledge-driven Contrastive Learning (SKCL) uses a language model to decide which classes are related, and pulls each image towards the protot

researcharxiv-cs-cv

Where mission meets moonshot: Join us at the Google Public Sector Summit 2026

model-releasesgoogle-cloud-ai

Across the public sector, the question has shifted from “what’s possible?” to “how can we drive mission impact?” We’ll be answering this question at the Google Public Sector Summit on October 20th at

Local Ai

Which Ollama MLX model for medical stuff, charts etc?

Hi, I'm on M4 Pro 64GB Mac, I'm using Qwen3.8 27B for coding related stuff, but it's quite slow. I want a fast model that will be good when it comes to reasoning, medical stuff, would be nice if it co

local-air-ollama

Which Preferences to Train On? End-to-End Multi-Objective Alignment with an Adversarial Preference Distribution

arXiv:2610.04845v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multif

safetyarxiv-cs-lg

Why 38% of AI Agent container escapes didn't need kernel 0-days: Analysis of 109 empirical incidents (Open Dataset + Defense Harness)

model-releasesr-localllama

Over the past several months, we conducted an empirical post-mortem investigation into 109 autonomous AI agent security incidents (cataloged with 193 falsification criteria across tool-use and multi-a

Why Convolution Still Matters: Evaluating Inductive Biases in Cryospheric Image Classification

arXiv:2610.04073v1 Announce Type: new Abstract: Recent advances in attention-based deep learning have motivated their adoption for remote sensing image classification; however, their benefits for cryo