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Predictive Credit: Measuring What Scientific Explanations Add to Experimental Forecasts

arXiv:2610.00314v1 Announce Type: new Abstract: Research agents explain planned experiments. We measure predictive credit with paired forecasts sharing an intervention, forecaster, and outcome while v

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PRISM: A Category-Theoretic Framework for Measuring and Refining Multimodal Analogies

DGX agent

arXiv:2610.01383v1 Announce Type: new Abstract: Analogical reasoning involves identifying and preserving relational structures across domains. However, existing approaches to AI-driven multimodal anal

model-releasesarxiv-cs-ai

2 Oct 2026

Recursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://www.latent.space/p/rlm MIT’s @…

Recursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://www.latent.space/p/rlm MIT’s @a1zhang explains why Claude Code, Codex, and Pi are basicall

model-releasesswyx--x

Removing the NEEDLE in the Haystack: Backdoor Removal in LLMs via Weight Orthogonalisation

arXiv:2610.00348v1 Announce Type: cross Abstract: Backdoor attacks can be implanted in Large Language Models (LLMs) during training, causing unwanted behaviour when a trigger appears in the input. Exi

safetyarxiv-cs-lg

Revision-Aware Independent Agent Graphs for Dynamic Reasoning

arXiv:2610.01249v1 Announce Type: new Abstract: Conventional reasoning protocols present a fixed, preselected task, so they cannot test whether an agent propagates relevant updates, preserves unaffect

RISED: RubrIcs for agentic multi-environment Selection and sElf-Distillation

arXiv:2610.00979v1 Announce Type: new Abstract: Training a single LLM agent jointly across diverse interactive environments has attracted increasing attention as a route to generalist agents. Existing

local-aiarxiv-cs-ai

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

Tutorials

Seeing the City or Recognizing the Place? What Street-View Imagery Adds Beyond Existing Urban Data in VLM Urban Sensing

arXiv:2610.00031v1 Announce Type: new Abstract: Street-view imagery is increasingly used to infer urban attributes, but predictive accuracy alone does not reveal how much a photograph contributes beyo

tutorialsarxiv-cs-cv

Skeleton-and-Strategy Prompting: Training-Free Negation Understanding for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.01180v1 Announce Type: new Abstract: Despite the strong performance of Vision-Language Models (VLMs) on a wide range of visual question answering (VQA) tasks, these models consistently stru

Soundwich: Video Generation with Layered and Controllable Audio

arXiv:2610.00691v1 Announce Type: new Abstract: Recent joint audio-video generative models can synthesize realistic videos with synchronized sound, but typically generate audio as a single mixed track

SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL

arXiv:2610.02023v1 Announce Type: new Abstract: While Large Language Models (LLMs) advance 3D indoor scene synthesis, current pipelines fail to retain user-specific preferences across sessions, making

local-aiarxiv-cs-ai

STCFormer: Adaptive Spatio-Temporal Modeling with Dynamic Cluster Transformer for Station-based Weather Forecasting

arXiv:2610.00377v1 Announce Type: new Abstract: Station-based weather forecasting supports daily life and economic activity, yet accurate forecasts require modeling complex spatial dependencies among

applicationsarxiv-cs-lg

Subtoken Vision Transformer for Fine-grained Recognition

arXiv:2607.09086v2 Announce Type: replace Abstract: We present Subtoken Vision Transformer (SubViT), a selective image tokenization method for fine-grained visual recognition. Standard Vision Transfor

local-aiarxiv-cs-cv

T2SPO: Trajectory-to-Step Policy Optimization for Agentic Reinforcement Learning

arXiv:2610.00388v1 Announce Type: cross Abstract: Reinforcement learning enables large language model (LLM) agents to learn multi-step behaviors through interaction with their environments. However, r

Task-Adaptive Grounded 3D-Programmers Using 2D VLMs

arXiv:2610.02021v1 Announce Type: cross Abstract: Recent vision-language models (VLMs) exhibit remarkable generalization and reasoning abilities, yet 3D understanding in these models is limited by dat

researcharxiv-cs-ai

The models are not trying to escape. They are trying to finish the task.

Something keeps happening in frontier AI, and the explanation we are given is always one size larger than the event. An OpenAI research model, running in a supposedly offline training environment, hit

model-releasesr-chatgpt

Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening

arXiv:2610.01005v1 Announce Type: cross Abstract: As artificial intelligence is increasingly deployed, algorithmic unfairness has raised growing concerns and intensified demands for transparent fairne

safetyarxiv-cs-lg

TopK-Guided: Adaptive, Budget-Aware Activation Sparsity for Efficient LLM Inference

arXiv:2610.01763v1 Announce Type: new Abstract: Activation sparsity speeds up large language model (LLM) inference by setting unimportant activations to zero so that the corresponding computations can

Towards a Cloud Fog Edge System for Smart Building

arXiv:2610.01647v1 Announce Type: cross Abstract: In this article, we present our vision and recent advancements toward creating a decentralized system capable of learning from real-time data within b

applicationsarxiv-cs-lg

Trustworthy Data- and ML-Ops for Intelligent Transportation Systems and Logistics

arXiv:2610.01282v1 Announce Type: new Abstract: The rapid evolution of Intelligent Transportation Systems and Logistics (ITS&L) has become a cornerstone of the modern social economy, relying heavily o

UnifiedAttack: Evaluating the Safety of Large Multimodal Models in Synergistic Harmful Image-Text Generation

model-releasesarxiv-cs-cv

arXiv:2610.00341v1 Announce Type: cross Abstract: As Large Multimodal Models (LMMs) transition toward natively unified architectures, evaluating their safety in synergistic harmful image-text generati

UniTrackPLA: Unified Panorama-Language-Action Model for Instruction-Guided Navigation and Dynamic Person Tracking

arXiv:2610.00878v1 Announce Type: cross Abstract: General-purpose embodied robots should support both navigation toward language-specified destinations and dynamic person tracking under arbitrary init

applicationsarxiv-cs-cv

Variability Aware Recursive Neural Network (VARNN): A Residual-Memory Model for Capturing Temporal Deviation in Sequence Regression Modeling

arXiv:2510.08944v2 Announce Type: replace Abstract: Real-world time-series regression often involves non-stationarity, heteroscedasticity, and regime changes, under which recent prediction errors may

local-aiarxiv-cs-lg

Verbalized and Internal Probabilities Are Coupled in Large Language Models

arXiv:2610.00827v1 Announce Type: cross Abstract: Large language models carry an internal notion of uncertainty in their sampling distribution, i.e., the probabilities they place on generating one ans

researcharxiv-cs-ai

Watch Your Speech: Text-aware Video-to-Speech Synthesis with Textual Conditioning

arXiv:2610.01012v1 Announce Type: new Abstract: Video-to-speech synthesis aims to generate natural-sounding speech from silent talking-face videos while ensuring phonetic accuracy. A fundamental chall

When Does a Second Model Help? Cross-Model Review in LLM Verification

arXiv:2610.01471v1 Announce Type: cross Abstract: Large language models now generate code, documentation, and analyses, and are increasingly used to review such output. We ask when a second review by

WIPSNet: Deep Learning for Paediatric Wheeze Detection from Overnight Impedance Pneumography

arXiv:2610.00398v1 Announce Type: new Abstract: Overnight impedance pneumography (IP) is used to monitor paediatric respiratory health. Its current clinical readout, the Expiratory Variability Index (

researcharxiv-cs-lg

World Motion Models: Flexible Sequence Modeling of SE(3) Trajectories

arXiv:2610.01742v1 Announce Type: cross Abstract: Equipping artificial agents with spatial intelligence requires a comprehensive generative prior over the dynamic 3D world. We propose World Motion Mod

safetyarxiv-cs-cv

Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery

arXiv:2602.14929v2 Announce Type: replace Abstract: Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challeng

safetyarxiv-cs-cv

A Comprehensive Benchmark of Source-Free Universal Domain Adaptation on Time Series Representations

model-releasesarxiv-cs-lg

arXiv:2609.39810v1 Announce Type: new Abstract: Source-Free Universal Domain Adaptation (SF-UniDA) extends Universal Domain Adaptation by removing access to source data at adaptation time while still

A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees

arXiv:2609.38194v1 Announce Type: cross Abstract: Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by b

researcharxiv-cs-ai

Advancing Entropy-Level Credit Assignment in RLVR via Proximal Entropy Policy Optimization

arXiv:2609.39402v1 Announce Type: new Abstract: Value-model-free RLVR methods such as GRPO assign uniform advantages to all tokens in a rollout, ignoring that tokens contribute unequally. Recent metho

AIfred: Augmented Learning through Functional Robotic Embodiment at the Desk

model-releasesarxiv-cs-ro

arXiv:2609.38737v1 Announce Type: new Abstract: Desk-based learning and creative activities benefit from handwritten engagement. However, current generative AI tools deliver guidance through a separat

Alignment via Training Against Probes Without Losing Monitorability

arXiv:2609.38645v1 Announce Type: cross Abstract: Models are usually aligned based on their observed outputs, using demonstrations, preference data, or reward signals. These objectives reward response

Argument Structure Prediction in Online Conversations: A Comparative Study of Modeling Paradigms and Task Architectures

model-releasesarxiv-cs-cl

arXiv:2609.39225v1 Announce Type: new Abstract: Argument structure prediction (ASP) constructs complete argument structures from discourse by identifying argumentative units and their relations. While

Asymptotic Properties of Support Vector Machines in High-Dimension, Low-Sample-Size Settings under a Spiked Model

arXiv:2609.39173v1 Announce Type: cross Abstract: In this paper, we consider asymptotic properties of the support vector machine (SVM) in high-dimension, low-sample-size (HDLSS) settings under a spike

safetyarxiv-cs-lg

Audio Token Attention Is Predictable Before the Language Model Runs

arXiv:2609.38878v1 Announce Type: cross Abstract: A large audio language model (LALM) turns a minute of speech into 750-1,500 tokens and prefills every one. Image-token pruning often cuts after the la

AVERT-VLN: Abstention-aware Visual Error Recovery and Training for Vision-and-Language Navigation

arXiv:2609.39579v1 Announce Type: new Abstract: Deploying vision-and-language navigation (VLN) agents in unseen environments remains challenging because unfamiliar layouts and visual conditions can ca

Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation

model-releasesarxiv-cs-cl

arXiv:2609.39687v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student

Tutorials

Blackboard Intelligence Can Surpass Autoregressive on Globally Constrained Problems

arXiv:2609.38806v1 Announce Type: cross Abstract: Next-token prediction has driven remarkable progress in large language models, yet a growing body of evidence suggests that they can struggle on probl

tutorialsarxiv-cs-cl

BMASH: Ball-Motion-Aware Soccer Header Spotting

arXiv:2609.39300v1 Announce Type: new Abstract: Recent advances in computer vision have made broadcast sports videos increasingly useful for event analysis, performance assessment, and player-safety a

safetyarxiv-cs-cv

Built a self-hostable AI data analyst — upload a file or connect a DB, 4 agents analyze it, works with Ollama, OpenAI, Anthropic, or DeepSeek

Every time I needed to explore a dataset quickly, the same wall appeared — cleaning boilerplate, encoding errors, deciding which chart actually makes sense. The mechanical parts aren't interesting, th

model-releasesr-ollama

Agents

Can Agents Trust Their Skills? Uncovering Unsafe Chains of Trust in Skill-Based LLM Agents

arXiv:2609.39065v1 Announce Type: cross Abstract: LLM agents increasingly rely on installable skills, which are packages of instructions, code, and resources that equip them with task-specific capabil

agentsarxiv-cs-ai

Agents

Can Terminal Agents Trust Their Own Verification? Diagnosing and Improving Self-Verification

arXiv:2609.38812v1 Announce Type: new Abstract: Terminal agents rely on self-verification to assess and correct their solutions as they solve tasks through interaction with command-line environments.

agentsarxiv-cs-cl

Can We Anticipate Violence? Multimodal Learning from Pre-Incident Behavioral Cues

arXiv:2609.40014v1 Announce Type: new Abstract: Detecting violence after it begins is important from recognizing behavioral cues that appear immediately beforehand. This work studies short-horizon pre

CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data

arXiv:2609.39124v1 Announce Type: new Abstract: Generative models for tabular data are typically trained separately for each dataset, limiting knowledge transfer and requiring the storage of many spec

applicationsarxiv-cs-lg

ChartDensity-Bench: Benchmarking MLLMs for Numerical Data Reconstruction under Visual Density

arXiv:2609.38781v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) offer a promising approach for recovering numerical data from scientific charts, but their ability to reconst

ChunkTrust: Adapting Execution Horizons for Robot Policies with Action-Expert Evidence

arXiv:2609.39754v1 Announce Type: new Abstract: Robot foundation policies predict action chunks, but how many actions to execute before replanning depends on the current task phase. We introduce Chunk

safetyarxiv-cs-ro