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Identifying Neural Source Dynamics from Unknown Local Interventions

arXiv:2609.35379v1 Announce Type: new Abstract: Electroencephalography (EEG) records mixtures of brain-source activity. Even with a known anatomical forward model, experiments that excite only part of

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Human DGX agent

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Identifying Temporal Features within Transcoders for Time Sensitive Factual Recall

DGX agent

arXiv:2609.33183v1 Announce Type: cross Abstract: Large Language Models (LLMs) suffer from temporal misalignment, often due to the contradictory nature of their training corpora. While current mitigat

model-releasesarxiv-cs-lg

29 Sept 2026

Identifying the Predictable Drift of a Semimartingale from Marginal Laws

arXiv:2609.33372v1 Announce Type: cross Abstract: A special semimartingale admits a unique decomposition X=X_0+M+A into a local martingale M and a predictable finite-variation part A. We consider the

ILP-BO: Integer Linear Programming-Based Black-Box Optimization

arXiv:2609.33131v1 Announce Type: new Abstract: Black-box Optimization (BO) is a powerful framework for optimizing expensive objective functions or unknown functions with a limited number of evaluatio

Impact of Patient Orientation in Single- and Multi-View Camera Environments for AI-based Rehabilitation Monitoring

arXiv:2609.35726v1 Announce Type: new Abstract: Automated quality assessment of rehabilitation exercises relies heavily on accurate human pose estimation from video data. Although numerous RGB-based p

Improving Causal Effect Estimation of Weighted RegressionBased Estimator using Neural Networks

arXiv:2110.15075v2 Announce Type: replace Abstract: Estimating causal effects from observational data informs us about which factors are important in an autonomous system, and enables us to take bette

agentsarxiv-cs-lg

Tutorials

Improving Generative Model Self-Training with Geometrically Modified Outputs

arXiv:2609.35512v1 Announce Type: new Abstract: Self-training generative models - the continued improvement of a model using its own outputs - is becoming increasingly important as high-quality traini

tutorialsarxiv-cs-lg

Improving Test-Time Scaling with Adaptive Looped Transformers

arXiv:2609.35748v1 Announce Type: cross Abstract: Looped transformers have demonstrated promising parameter efficiency by reusing layers for latent computation. Prior studies compare looped and non-lo

Improving the Diversity of LLM Outputs without a Trade-off

arXiv:2609.33038v1 Announce Type: cross Abstract: We propose DAST (Diversifying Arithmetic Sampling with TokenTour), a method that increases the diversity of LLM outputs without any change to the marg

Improving Video Sparse Attention with Fine-grained Router and Sparse Rebasing

arXiv:2609.32882v1 Announce Type: new Abstract: We present VSA2, a frontier trainable sparse attention for video DiTs. VSA2 includes a variety of new architectural features and training procedures tha

Hardware

In-Flight KV Cache with Clean Anchors for Faster Autoregressive Video Diffusion

arXiv:2609.32540v1 Announce Type: new Abstract: Few-step autoregressive video diffusion generates a long video by splitting the video into temporal chunks and generating chunk-by-chunk, each through a

hardwarearxiv-cs-cv

Applications

In-game Toxic Detection: Bi-directional Representations with Attention Residuals

arXiv:2609.34584v1 Announce Type: cross Abstract: In-game toxic language has emerged as a critical concern in the gaming industry and community. While several frameworks and models for online game tox

applicationsarxiv-cs-lg

Applications

In-Token Learning for High-Fidelity Image Restoration via Diffusion Transformers

arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C

applicationsarxiv-cs-cv

Inductive Feedback for Mixed-Policy Distillation

arXiv:2609.35390v1 Announce Type: new Abstract: Verbal feedback can identify errors and prescribe corrections, providing rich supervision for language-model post-training even when reliable programmat

Inertia-Corrected Newton Method For Generalized Nash Equilibria in Dynamic Games with Optimality Verification

arXiv:2609.31929v1 Announce Type: new Abstract: Newton methods efficiently find Generalized Nash Equilibria (GNE) in dynamic games by solving for the KKT necessary conditions. These methods are fast a

agentsarxiv-cs-ro

InfiMed2: A Generalist Medical Multimodal Foundation Model from Contextual Evidence and Stability-Aware Supervision

arXiv:2609.34798v1 Announce Type: cross Abstract: Recent medical multimodal models have benefited from larger corpora, broader modality coverage, and stronger reasoning-oriented training, yet effectiv

InfiniHand: Streaming World-Space Hand Motion Estimation from Egocentric Video

arXiv:2609.35743v1 Announce Type: new Abstract: World-space hand motion estimation from egocentric video requires recovering 3D articulated hand geometry while tracking camera egomotion. Existing appr

InfoEdit: Probing Global Layout Reasoning in Infographic Editing

arXiv:2609.33286v1 Announce Type: new Abstract: Multimodal foundation models edit natural photographs at production quality, yet the same models struggle with structured visual content such as infogra

Information Design Against Gaming and Learning Adversaries

arXiv:2609.31643v1 Announce Type: new Abstract: A principal who deploys a binary classifier with an abstention option must decide which queries the mechanism abstains on. The right choice depends on t

Information-Theoretic Analysis of Next-Token Prediction under Markovian Data

arXiv:2609.34731v1 Announce Type: cross Abstract: We develop an information-theoretic framework for generalization in next-token prediction under temporally dependent data. We consider independent tra

Informative Viewpoint Selection for Episodic-Memory Embodied Question Answering using Omnidirectional Images

arXiv:2609.33288v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires agents to answer natural language questions about surrounding environments from visual observations. In this

agentsarxiv-cs-cv

InfraVLA: Extending Vision-Language-Action Navigation with Infrastructure Cameras

arXiv:2609.33647v1 Announce Type: new Abstract: Many indoor environments in which robots operate, such as warehouses, offices, and hospitals, already have cameras installed. They observe parts of the

safetyarxiv-cs-ro

Inspection-SPARS: Task-Oriented Sparse Roadmaps for Inspection Planning

arXiv:2609.35516v1 Announce Type: new Abstract: Inspection planning seeks a minimum-length collision-free robot tour that observes a given set of points of interest (POIs). Sampling-based methods redu

researcharxiv-cs-ro

Inspector: Conversational and Lightweight Analyzer of Analog Circuit Layouts Using LLM and CNNs

arXiv:2609.34976v1 Announce Type: cross Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs)

Instance-Adaptive Prompts as Context for Time-Series Foundation Models

arXiv:2609.34786v1 Announce Type: new Abstract: Longer histories can improve time-series foundation models (TSFMs), but require substantially higher inference cost. We therefore ask whether contextual

Instance-optimal high-precision shadow tomography with few-copy measurements: A metrological approach

arXiv:2602.04952v2 Announce Type: replace-cross Abstract: We study the sample complexity of shadow tomography in the high-precision regime under realistic measurement constraints. Given an unknown d-d

Instruct, Not Answer: Using Instruction Privileges in On-Policy Context Distillation

arXiv:2609.32201v1 Announce Type: cross Abstract: On-Policy Context Distillation (OPCD) has recently emerged as a powerful technique for transferring context to student models and for self-improvement

Integrated Deep Learning Framework Designed on Hybrid Optimization Strategies for Automated Health Detection and Analysis in Silkworms

arXiv:2609.31701v1 Announce Type: new Abstract: A Hybrid Residual Attention Network is proposed for accurately classifying silkworm images into six different classes, including healthy and diseased st

Integrating Language Models into Listened and Imagined Speech Decoding from MEG

arXiv:2609.31997v1 Announce Type: new Abstract: Decoding imagined speech is an important goal for brain-computer interfaces but remains challenging due to weak neural responses, low signal-to-noise ra

Integrity Detection and Characterization of Malicious Injections in RAVEN II

arXiv:2609.33951v1 Announce Type: new Abstract: The increasing adoption of robotic systems in surgery, together with the expanding range of procedures they can support and the growing level of autonom

safetyarxiv-cs-ro

Interactive Distributionally Robust Multi-Agent Learning with General Function Approximation

arXiv:2609.32048v1 Announce Type: new Abstract: Model misspecification poses a fundamental challenge in multi-agent reinforcement learning, where transition uncertainty can be amplified by strategic i

agentsarxiv-cs-lg

Interference Beyond Geometry in Concept Extraction

arXiv:2609.35351v1 Announce Type: new Abstract: Interference is commonly treated as geometric overlap between learned features. We introduce effective interference, which combines feature geometry and

Interp3R: Continuous-time 3D Geometry Estimation with Frames and Events

arXiv:2603.14528v2 Announce Type: replace Abstract: In recent years, 3D visual foundation models, pioneered by pointmap-based approaches such as DUSt3R, have attracted a lot of interest, achieving imp

Interpretable Physics Informed WiFi Indoor Localization: Learning an Effective Access Point Geometry and Using It to Prune

arXiv:2609.32539v1 Announce Type: cross Abstract: Deep learning models can achieve high accuracy for indoor localization, but their black-box nature limits interpretability and the reuse of learned in

Interrelating Fruchterman-Reingold Graph Visualization and Agglomerative Clustering

arXiv:2609.35073v1 Announce Type: new Abstract: Graph visualization methods and agglomerative clustering have been frequently considered in data analysis and pattern recognition. Because these approac

InterTab: Interleaved Visual-Structure Alignment for Multi-Modal Table Reasoning

arXiv:2609.32660v1 Announce Type: new Abstract: Table images preserve structural information that are often lost in text serialization, and reasoning over them requires locating relevant rows, columns

Intuition vectors

arXiv:2609.32619v1 Announce Type: new Abstract: Large self-supervised vision models learn representations that support scene segmentation and the semantic decomposition of physical objects. We ask whe

Investigating the Effect of k-NN Preprocessing on Developing Graph Neural Networks: A Fairness-Based Perspective

arXiv:2609.33416v1 Announce Type: new Abstract: In this paper, a methodology to design fair graph convolutional neural networks (GCNs) is developed and tested over several application data sets. The g

Is H&E Image-to-Spatial Transcriptomics Simpler Than It Looks?

arXiv:2609.32857v1 Announce Type: new Abstract: Predicting spatial gene expression from routine H&E histology offers a scalable route toward spatial molecular profiling. Recent work has pursued increa

Is invariance all you need for algorithmic fairness? Removing demographic information can create new bias

arXiv:2609.32004v1 Announce Type: new Abstract: Encoded demographic information in internal model representations is a commonly assumed risk factor for algorithmic bias, with demographic representatio

Is Online Interaction Necessary for Recovery? A Minimalist Approach to Robust Planning via Perturbation

arXiv:2609.33049v1 Announce Type: new Abstract: Behavior cloning (BC) is vulnerable to covariate shift during closed-loop execution, where small prediction or execution errors can drive the robot towa

safetyarxiv-cs-ro

IVT-Guard: All-in-One Reasoning Model for AI-Generated Content Detection

arXiv:2609.33585v1 Announce Type: new Abstract: The rapid proliferation of highly realistic AI-Generated Content (AIGC) necessitates robust and interpretable detection mechanisms. However, existing de

Jailbreaks for Black-Box Uncertainty Quantification in Large Reasoning Models

arXiv:2609.35350v1 Announce Type: cross Abstract: While Large Reasoning Models (LRMs) excel at complex reasoning, alignment through reinforcement learning often induces systemic overconfidence. In pro

JazzSAMBA: A Synchronous and Asynchronous Multi-take Band Audio Dataset of Jazz Standards for Live Music Models

arXiv:2609.34931v1 Announce Type: cross Abstract: Machine learning has made strong progress on music tasks, both as assistive tools and as creative partners. However, most systems train on multitrack

Hardware

JEPA Learns What the Mask Leaves Unrecoverable

arXiv:2609.32481v1 Announce Type: new Abstract: Joint-embedding predictive architectures are unusually sensitive to how the input is masked: block masks work, scattered masks do not, and the explanati

hardwarearxiv-cs-cv

JET: Justification Evaluation in Transformer

arXiv:2609.33874v1 Announce Type: new Abstract: JET uses pretrained language and vision-language models to select among a finite set of answers without additional training. It evaluates candidate like

Jev in Medicine: A Benchmark Evaluation. Preliminary Results

arXiv:2609.34024v1 Announce Type: cross Abstract: Jev is a non-generative 'System One' model that assigns probabilities to predefined answer options and cannot answer outside them. Its accuracy and ca

JIVE: Jacobian-Informed Volume Expansion for Diverse Generative Sampling

arXiv:2609.33906v1 Announce Type: cross Abstract: Generative models often suffer from mode collapse and limited sample diversity. While prior works attempt to mitigate this by jointly generating a bat