Search: “pretraining”

ProtoLIP: From Sentence-Level to Object-Level Evidence Disentanglement

arXiv:2609.16284v1 Announce Type: cross Abstract: Query-conditioned vision--language models enable fine-grained interpretation by revealing how visual evidence changes with textual queries. However, e

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Research

Repurposing Deep Limit Order Book Forecasting for Scenario-Conditioned Market Impact Modeling

DGX agent

arXiv:2609.16930v1 Announce Type: cross Abstract: Deep Limit Order Book forecasting models capture nonlinear market dynamics, but their ability to quantify the effects of counterfactual order book mes

researcharxiv-cs-ai

16 Sept 2026

SAVLA: Symmetry-Aware Vision-Language-Action Models for Robotic Manipulation

arXiv:2609.16641v1 Announce Type: new Abstract: Vision-language-action (VLA) models have become the dominant paradigm for language-conditioned robot manipulation. However, although images and language

safetyarxiv-cs-ro

SITA: Learning Speaker-Invariant and Tone-Aware Speech Representations for Low-Resource Tonal Languages

arXiv:2601.09050v2 Announce Type: replace Abstract: Tonal low-resource languages are widely spoken but remain underserved by modern speech technologies. A central challenge is learning speech represen

researcharxiv-cs-cl

SPEAR NeXT Causal Latent Forecasting Across Multiple Horizons for Spectral Temporal Earth Representation Learning

arXiv:2609.16871v1 Announce Type: new Abstract: Earth observation is inherently dynamic, yet temporal information in many foundation models is learned through reconstruction, invariance, or retrospect

SyncVoice: Simple and Effective Automatic Video Dubbing with Vision-Augmented TTS

arXiv:2512.05126v2 Announce Type: replace-cross Abstract: Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still

TEMPO: Learning Temporal Context for Dynamic Robot Manipulation

arXiv:2609.16864v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved impressive performance in quasi-static manipulation, but struggle in dynamic manipulation tasks beca

The record is part of the task: matched-record evaluation of text classifiers across maintenance, safety and recall reporting

arXiv:2609.16267v1 Announce Type: cross Abstract: Many operational cases are documented more than once, at different workflow stages and for different purposes, yet model evaluations normally select o

safetyarxiv-cs-cl

What Does Layer-Importance Reveal About Transformers and State-Space Models?

arXiv:2609.16537v1 Announce Type: cross Abstract: Transformers and state-space models (SSMs) are the two dominant families of sequence models, and a central open question is how far the analytical kno

Window-Diffusion: Accelerating Diffusion Language Model Inference with Windowed Token Pruning and Caching

arXiv:2601.20332v3 Announce Type: replace Abstract: Diffusion language models (DLMs) generate text through iterative denoising, but inference requires full-sequence attention at every iteration, resul

local-aiarxiv-cs-lg

Tutorials

A Chosen Future Can Still Be Rewritten: Causal Writability in Video Models

arXiv:2609.15980v1 Announce Type: cross Abstract: When a video model generates physically incorrect motion, did it fail to learn the correct motion, or did it learn it but fail to use it? We show the

tutorialsarxiv-cs-cv

A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis

arXiv:2609.15740v1 Announce Type: cross Abstract: Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-e

A property-registry contract for retrieve-or-refuse thermal-mechanical lattice search

model-releasesarxiv-cs-ai

arXiv:2609.14741v1 Announce Type: cross Abstract: Early thermal-mechanical lattice requirements are knowledge-intensive and often jointly unsatisfiable: an engineer asks for a cell that is light, stif

A Unified Vision-Language Model for PSMA PET/CT Report Generation, Visual Question Answering, and Lesion Segmentation

arXiv:2609.15603v1 Announce Type: cross Abstract: Accurate PSMA PET/CT interpretation is central to prostate cancer management, yet existing PET/CT AI models typically address isolated tasks. We propo

Accuracy Is Not Service: A Decision-Aware Benchmark for Intermittent-Demand Forecasting

model-releasesarxiv-cs-lg

arXiv:2609.13840v1 Announce Type: new Abstract: A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are

Tutorials

AG-EgoPose: Spatially Anchored Residual Correction with Action Context for Monocular Egocentric 3D Pose Estimation

arXiv:2603.25175v2 Announce Type: replace Abstract: Monocular egocentric 3D pose estimation is difficult because severe foreshortening, self-occlusion, and a restricted field of view often remove the

tutorialsarxiv-cs-cv

AlayaVista: Streaming World Modeling from Panoramic States to Perspective Video

arXiv:2609.14462v1 Announce Type: new Abstract: Interactive video world models must maintain broad scene context under camera motion while producing high-fidelity observations with low latency. Existi

local-aiarxiv-cs-cv

An Efficient and Modular Framework for Targeted Harm Mitigation in LLMS

arXiv:2609.13624v1 Announce Type: cross Abstract: Large Language Models (LLMs) are powerful zero-shot learners but remain prone to misalignment with human preferences, often producing biased, toxic, o

BEACON: Behavior and Appearance Control for Subject-Specific Video Generation

arXiv:2609.13264v1 Announce Type: cross Abstract: Generating human-centric videos that preserve both visual identity and person-specific expressive behavior remains a fundamental challenge. In additio

Beyond Accuracy: Robustness, Cost, and Governance Trade-offs for Vision-Language Models in Templated Document Extraction

model-releasesarxiv-cs-ai

arXiv:2609.15706v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to extract structured fields from business documents, yet most evaluations report accuracy on clean

Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment

arXiv:2602.01257v2 Announce Type: replace Abstract: Recently, point-supervised temporal action localization has gained significant attention for its effective balance between labeling costs and locali

local-aiarxiv-cs-cv

Can a Neural Encoding Model Replicate an fMRI Visualization Study?

arXiv:2609.15685v1 Announce Type: cross Abstract: Most knowledge of graphical perception comes from behavioral studies. Understanding from a neural perspective is much more limited due in part to neur

safetyarxiv-cs-cv

Chance-Constrained Belief-Space Maneuver Planning for Autonomous Collision Avoidance Under Uncertainty

arXiv:2609.13428v1 Announce Type: cross Abstract: Increasing conjunction frequency in low Earth orbit places growing pressure on spacecraft operators to determine not only whether an encounter require

agentsarxiv-cs-ai

Compositional Shift Algebra: Extrapolating Mixed Robot Shifts Without Mixed Finetuning

arXiv:2609.13651v1 Announce Type: cross Abstract: Robot deployments rarely change one mechanism at a time: cameras, action interfaces, and physical dynamics often shift together. Prior adaptation reci

CRAF: Cross-View Residual-Aware Fusion for Deepfake Speech Detection

arXiv:2609.13842v1 Announce Type: cross Abstract: Recent advances in speech synthesis and voice conversion have made deepfake speech increasingly realistic, making generalization to unseen spoofing at

Data Efficient Any Transformer-to-Mamba Distillation via Attention Bridge

arXiv:2510.19266v3 Announce Type: replace Abstract: State-space models (SSMs) have emerged as promising alternatives to Transformers for sequence modeling. However, training competitive SSMs from scra

safetyarxiv-cs-lg

Applications

DIDO: Distilling Interaction-Centric Dynamics into One-Step Denoising for World Action Models

arXiv:2609.15570v1 Announce Type: new Abstract: World Action Models (WAMs) use video generation models to predict future visual dynamics for robotic manipulation, but iterative denoising introduces ad

applicationsarxiv-cs-ro

Diffusion Trajectory Modeling for Semantic Correspondence

arXiv:2609.15357v1 Announce Type: new Abstract: Diffusion models generate images through an iterative diffusion process, and recent studies have demonstrated that the intermediate feature maps produce

Discrete Beckmann Transport Models for One-Step Language Modeling and Reasoning

arXiv:2609.15903v1 Announce Type: new Abstract: Discrete diffusion and flow models are a promising alternative to autoregressive language models, but compressing many-step sampling into fewer steps ty

agentsarxiv-cs-lg

DuoTok: Source-Aware Dual-Track Music Tokenization for Vocal-Accompaniment Generation

arXiv:2511.20224v3 Announce Type: replace-cross Abstract: Multi-track music generation requires tokens that preserve acoustic fidelity, support sequence modeling, and maintain cross-track structure. R

Exploring Multimodal Turn-Taking Cues in Face-to-Face Conversation using Voice Activity Projection

arXiv:2609.14666v1 Announce Type: cross Abstract: Turn-taking is a fundamental component of spoken interaction, and while humans naturally rely on both verbal and non-verbal signals, dialogue systems

researcharxiv-cs-cl

FICAug: Feature-Informed Clustering and Augmentation for Facial-Expression-Based Parkinson's Disease Screening

arXiv:2409.17685v3 Announce Type: replace Abstract: Hypomimia has drawn growing interest as a digital marker for screening Parkinson's disease (PD). However, developing reliable facial-expression-base

GLAM: Training a latent world model over global spatiotemporal memory for active exploration and navigation

arXiv:2609.14561v1 Announce Type: new Abstract: Active exploration and semantic navigation require an embodied agent to build memory from partial observations, predict how the evolution of observed sp

agentsarxiv-cs-ro

GorillaWatch: An Automated System for In-the-Wild Gorilla Re-Identification and Population Monitoring

arXiv:2512.07776v2 Announce Type: replace Abstract: Monitoring critically endangered western lowland gorillas is currently hampered by the immense manual effort required to re-identify individuals fro

Tutorials

How to Better Train VLAs: Lessons Learned From the REAL-I Challenge at ICRA 2026

arXiv:2609.13679v1 Announce Type: new Abstract: How can robot policies learn more effectively from a fixed demonstration budget? The first Real-world Embodied AI Learning (REAL-I) Challenge at ICRA 20

tutorialsarxiv-cs-ro

IMM-based Multiple Object Tracking using a State Prediction Neural Network

arXiv:2609.13307v1 Announce Type: cross Abstract: Object tracking is essential for autonomous vehicles to avoid obstacles and plan routes. Radar maintains detection performance even in adverse weather

agentsarxiv-cs-ai

Land Art as a Big-Data Climate Sensor

arXiv:2609.13182v1 Announce Type: cross Abstract: Robert Smithson's 1970 land artwork Spiral Jetty, located in the north arm of Utah's Great Salt Lake, has alternated between submergence and exposure

MedVA: An End-to-End Neuro-Symbolic Agentic System for Medical Volume Visualization

arXiv:2609.14874v1 Announce Type: cross Abstract: Medical volume visualization requires selecting regions of interest (ROIs) and carefully controlling their relative visual emphasis according to a giv

agentsarxiv-cs-cv

MoME: Mixture-of-Memory Embeddings for Context-Aware Sparse Lookup

model-releasesarxiv-cs-ai

arXiv:2609.15126v1 Announce Type: cross Abstract: Scaling large language models efficiently has motivated sparse capacity mechanisms such as Mixture-of-Experts and, more recently, conditional memory:

MuPlon: Multi-Path Causal Optimization for Claim Verification through Controlling Confounding

arXiv:2509.25715v2 Announce Type: replace-cross Abstract: As a critical task in data quality control, claim verification aims to curb the spread of misinformation by assessing the truthfulness of clai

researcharxiv-cs-cl

Applications

Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement

arXiv:2607.14162v1 Announce Type: cross Abstract: Model-Based Systems Engineering (MBSE) relies on formal system models as primary technical artifacts for representing requirements, structure, and beh

applicationsarxiv-cs-ai

One Spectrum, Two Resources: Data-Memory Scaling in Autoregressive Prediction

arXiv:2609.13500v1 Announce Type: cross Abstract: How much learned memory is needed to benefit from more data? We show that the two resources are governed by one predictive-energy spectrum in a positi

Patient-Level, Leakage-Aware Deep Learning for Cross-Center Periapical Radiograph Classification

arXiv:2609.14703v1 Announce Type: new Abstract: Dental caries and endodontic disease are among the most common health conditions worldwide, and intraoral periapical radiographs are central to their de

PC^2-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices

arXiv:2609.14722v1 Announce Type: new Abstract: Low-cost and low-resolution sensors used in edge deployments can produce test point clouds that are substantially sparser than the normal training data.

Pixel-wise Planarity for High-Precision Monocular Plane Segmentation

arXiv:2609.13246v1 Announce Type: new Abstract: Plane segmentation from a single RGB image remains challenging due to imprecise region grouping and geometrically inconsistent supervision, often leadin

Applications

Predicting build orientation for SLM dental parts: a comparison of rotation representations and direct vector regression

arXiv:2609.15710v1 Announce Type: new Abstract: Build orientation for selective laser melting (SLM) manufacturing of dental parts is usually chosen manually by technicians. We treat orientation predic

applicationsarxiv-cs-ai

Realistic Continual Learning Approach using Pre-trained Models

arXiv:2404.07729v2 Announce Type: replace-cross Abstract: Continual learning (CL) evaluates adaptability in learning solutions to retain knowledge. Our research addresses the challenge of catastrophic

Restore What Matters: Lessons from Joint Restoration and Recognition

arXiv:2609.13791v1 Announce Type: new Abstract: Recognition pipelines typically adopt a restore-then-recognize workflow, yet decades of experience show that generating visually pleasing images seldom

safetyarxiv-cs-cv