Search: “pretraining”

SonoRank: Towards Calibration-Free Real-Time Finger Flexion Detection from Forearm Ultrasound Sequences

arXiv:2607.07542v1 Announce Type: cross Abstract: Powered prosthetic hands are frequently abandoned, largely due to the limited functionality of current devices that rely on surface electromyography (

9 Jul 2026

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Model Releases

TF-Engram: A Train-Free Engram with SSD-Backed Memory for Large Language Models

DGX agent

arXiv:2607.07388v1 Announce Type: new Abstract: Large Language Models (LLMs) store factual knowledge and domain-specific patterns implicitly in dense Transformer parameters, making knowledge expansion

model-releasesarxiv-cs-cl

9 Jul 2026

Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wild

arXiv:2607.06875v1 Announce Type: new Abstract: Understanding and forecasting audience reactions to video content are crucial for improving content creation, recommendation systems, and media analysis

9 Jul 2026

WAM-TTT: Steering World-Action Models by Watching Human Play at Test Time

arXiv:2607.06988v1 Announce Type: cross Abstract: Steering robot foundation models (RFMs) toward new task variants or user-preferred behaviors remains challenging, often requiring additional robot dem

researcharxiv-cs-ai

9 Jul 2026

A Constrained Optimization Perspective of Unrolled Transformers

arXiv:2601.17257v2 Announce Type: replace Abstract: We introduce a constrained optimization framework for training transformers that behave like optimization descent algorithms. Specifically, we enfor

AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking

arXiv:2607.05846v1 Announce Type: cross Abstract: Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery. However, existing methods

BlueMagpie-TTS: A Token-Efficient Tokenizer, Language Model, and TTS for Taiwanese-Accent Code-Switching Speech

model-releasesarxiv-cs-cl

arXiv:2607.06054v1 Announce Type: cross Abstract: Off-the-shelf TTS systems are poorly adapted to Taiwanese Mandarin. Their accent defaults to other Mandarin variants, their tokenizers over-segment co

Breaking Spurious Correlations via Generative Randomization and Cross-Variant Self-Supervised Learning

arXiv:2607.05850v1 Announce Type: new Abstract: Deep neural networks trained with Empirical Risk Minimization (ERM) often fail under distribution shifts because they exploit spurious correlations betw

tutorialsarxiv-cs-cv

Canopy: A Heterograph Foundation Model for Metabolic Engineering

arXiv:2607.06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering. Existi

tutorialsarxiv-cs-lg

Hardware

Design-CP: Context Parallelism for Design of Protein Nanoparticles

arXiv:2607.05439v1 Announce Type: new Abstract: Many all-atom generative protein models can in principle design large multimeric complexes by jointly modelling all chains, but their quadratic token- a

hardwarearxiv-cs-lg

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction

arXiv:2607.05568v1 Announce Type: cross Abstract: Representing 3D shapes as compact sets of geometric primitives is fundamental to robotics, simulation, and scene understanding. Generative image model

Industry Classification of GitHub Repositories Using the North American Industry Classification System (NAICS)

arXiv:2607.06505v1 Announce Type: cross Abstract: GitHub hosts hundreds of millions of public repositories, but the platform exposes no native mapping from repositories to standardized industry sector

Integrating GNSS-Derived Zenith Wet Delay into a Weather Foundation Model Improves Precipitation Forecasting

arXiv:2607.05658v1 Announce Type: cross Abstract: Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals.

LAMP: Latent Motion Prior-Guided Real-World Learning for Dexterous Hand Manipulation

arXiv:2607.06323v1 Announce Type: new Abstract: Real-world learning for dexterous hands remains brittle because high-dimensional hand actions amplify imitation errors and make reinforcement-learning e

safetyarxiv-cs-ro

Lift3D-VLA: Lifting VLA Models to 3D Geometry and Dynamics-Aware Manipulation

arXiv:2607.06564v1 Announce Type: cross Abstract: Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in

Massive open-source release! LingBot-Video isn't about video quality; it optimizes for physical reasoning, and it runs sparse: only 3B of 30…

Massive open-source release! LingBot-Video isn't about video quality; it optimizes for physical reasoning, and it runs sparse: only 3B of 30B params are active at inference. MoE is finally showing up

researchdair-ai--x

Perceptually Aligning Representations of Music via Noise-Augmented Autoencoders

arXiv:2511.05350v3 Announce Type: replace-cross Abstract: We argue that training autoencoders to reconstruct inputs from noised versions of their encodings, when combined with perceptually motivated l

researcharxiv-cs-ai

PhyMRI-SR: Toward Physics-Aware MRI Image Super-Resolution

arXiv:2607.06238v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) super-resolution is vital for improving diagnostic accessibility, yet most methods treat it as a deterministic mapping

Local Ai

SAMPLe: SAM-based Optimizer for Prompt Learning in VLMs

arXiv:2607.05727v1 Announce Type: new Abstract: Pre-trained Vision-Language Models (VLMs) like CLIP have proven highly effective as foundation models for various downstream applications. However, prom

local-aiarxiv-cs-cv

Transformers converge to invariant algorithmic cores

arXiv:2602.22600v2 Announce Type: replace-cross Abstract: Training selects for behavior, not circuitry: many weight configurations can implement the same function. Studying any single trained neural n

Vision as Unified Multimodal Generation

arXiv:2607.06560v1 Announce Type: new Abstract: We formulate computer vision as unified multimodal generation, where heterogeneous visual tasks are expressed in the native text and image generation sp

XRFormer: Multiscale Tokenization for XRF Representation Learning

arXiv:2607.06424v1 Announce Type: new Abstract: X-ray fluorescence (XRF) spectroscopy is a key modality for material analysis in cultural heritage. However, automated learning from XRF spectra remains

Adaptive Loss Balancing for Multi-Task Bioacoustic Classification of Bird Species and Call Types

arXiv:2607.03304v1 Announce Type: cross Abstract: Reliable analysis of bird vocalisations in passive acoustic monitoring requires models handling multiple, imbalanced annotation targets. We extend Bir

Adaptive Time-step Training for Enhancing Spike-Based Neural Radiance Fields

arXiv:2507.23033v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) provide an energy-efficient computing paradigm for neural rendering, but existing spike-based Neural Radiance Field (

AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis

arXiv:2512.11797v2 Announce Type: replace-cross Abstract: The collection of large-scale and diverse robot demonstrations remains a major bottleneck for imitation learning, as real-world data acquisiti

safetyarxiv-cs-cv

Asymptotic-Preserving A Posteriori Analysis of Diffusion and Flow-Matching Samplers

model-releasesarxiv-cs-lg

arXiv:2607.04113v1 Announce Type: new Abstract: Diffusion and flow-matching samplers integrate a learned probability-flow ODE from a large noise scale down to a small terminal floor sigma_{min}, at wh

Atlas is Your Perfect Context: One-Shot Customization for Generalizable Foundational Medical Image Segmentation

arXiv:2512.18176v2 Announce Type: replace Abstract: Accurate segmentation of anatomical structures in medical images is essential for diagnosis and treatment planning. While recent interactive segment

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation

arXiv:2607.02968v1 Announce Type: new Abstract: Massive Activations (MAs) have been widely observed in Transformer-based models, yet their structure and functional roles in Diffusion Transformers (DiT

Best-of-Better-N: Generating Pre-Aligned Responses with In-Context Learning

arXiv:2607.03453v1 Announce Type: cross Abstract: Inference-time alignment methods, such as Best-of-N, offer a flexible alternative to training-based alignment by using reward models to select high-qu

CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning

arXiv:2607.04619v1 Announce Type: cross Abstract: Modern automated audio captioning systems pair a frozen audio encoder with a large language model (LLM) via a trainable projector, incurring the encod

researcharxiv-cs-cl

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

safetyarxiv-cs-cv

CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts

arXiv:2607.03693v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced generalist robotic manipulation, yet real-world deployment reveals a fundamental challenge: robots are

safetyarxiv-cs-ro

CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recovery

arXiv:2607.03177v1 Announce Type: cross Abstract: Traditional reinforcement learning (RL) for recovery in autonomous systems lacks causal understanding and generalizes poorly to novel failure scenario

Local Ai

DELTA-TTS: Adapting Autoregressive Model into Diffusion Language Model for Text-to-Speech

arXiv:2607.04140v1 Announce Type: cross Abstract: Autoregressive (AR) text-to-speech (TTS) models generate discrete speech tokens sequentially, which makes inference slow and can degrade robustness by

local-aiarxiv-cs-cl

Diagnosing Aerial-View Object Detectors with Foundational Image Generative Models

arXiv:2607.02718v1 Announce Type: cross Abstract: Recent advances in large-scale image generative models enable photorealistic scene synthesis with controllable attributes. Beyond data augmentation, t

tutorialsarxiv-cs-ai

Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment

arXiv:2202.14019v3 Announce Type: replace-cross Abstract: Maintaining proper form while exercising is important for preventing injuries and maximizing muscle mass gains. Detecting errors in workout fo

tutorialsarxiv-cs-ai

DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation

arXiv:2607.04927v1 Announce Type: cross Abstract: World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense super

Dual-Adaptive SAM3: Hierarchical Routing over Low-Rank Expert Layers for Parameter-Efficient Medical Image Segmentation

arXiv:2607.02571v1 Announce Type: new Abstract: The Segment Anything Model with Concepts (SAM3) heralds a new paradigm for open-vocabulary segmentation through natural language interaction, offering s

DynaWM: A Base-VLA-Guided World Foundation Model for Moving-Object Manipulation

arXiv:2607.02604v1 Announce Type: new Abstract: Although vision-language-action (VLA) models have received widespread attention, many challenges remain in manipulating dynamic moving objects. In most

EGRA:Toward Enhanced Behavior Graphs and Representation Alignment for Multimodal Recommendation

arXiv:2508.16170v2 Announce Type: replace-cross Abstract: MultiModal Recommendation (MMR) systems have emerged as a promising solution for improving recommendation quality by leveraging rich item-side

Enhancing Video Physical Consistency via Role-aware Joint Training and Modality-decoupled Denoising

arXiv:2607.04653v1 Announce Type: new Abstract: While modern video diffusion models excel in visual fidelity, maintaining long-range physical consistency remains a formidable challenge. Conventional p

Explainable Novel Category Discovery in Semantic Concept Space

arXiv:2607.04548v1 Announce Type: cross Abstract: Novel category discovery aims to identify unseen classes from unlabeled data by transferring knowledge from labeled categories, but most existing meth

researcharxiv-cs-ai

FastCSP: Accelerated Molecular Crystal Structure Prediction with Universal Model for Atoms

arXiv:2508.02641v2 Announce Type: replace-cross Abstract: Molecular crystal structure prediction (CSP) is essential for applications in pharmaceuticals and organic electronics. However, CSP remains ch

From General Actions to Domain-Specific Monitoring: Prior-Adaptive Transfer for Skeleton-Based Action Recognition

arXiv:2607.03327v1 Announce Type: new Abstract: Skeleton-based action recognition models have recently shown strong performance on large-scale benchmarks with general actions. However, directly transf

G3Splat: Geometrically Consistent Generalizable Gaussian Splatting

arXiv:2512.17547v2 Announce Type: replace Abstract: 3D Gaussians have become a powerful scene representation for real-time splatting and high-quality novel-view synthesis. This has motivated generaliz

GeoSelect: Spatial-Program Execution for Training-Free Referring Remote Sensing Image Segmentation

arXiv:2607.03869v1 Announce Type: cross Abstract: Referring remote sensing image segmentation isolates the object named by a natural-language expression in an aerial image. Existing training-free meth

GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

model-releasesarxiv-cs-ro

arXiv:2607.02642v1 Announce Type: new Abstract: Evaluating embodied robot foundation models remains a critical bottleneck; unlike large language models efficiently assessed via digital benchmarks, rob

GlaBoost: A Multimodal Structured Framework for Glaucoma Risk Stratification

arXiv:2508.03750v2 Announce Type: replace-cross Abstract: Early and accurate glaucoma detection is critical to prevent irreversible vision loss, yet existing AI methods often rely on unimodal inputs a