Search: “pretraining”

Frozen Multimodal Embeddings for Personality and Cognitive Ability Assessment in Asynchronous Video Interviews

arXiv:2606.11930v1 Announce Type: cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging multimodal learning problem because labeled datasets are li

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GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction

DGX agent

arXiv:2606.11382v1 Announce Type: new Abstract: Deep learning models facilitate the discovery of molecules with tailored properties among billions of candidate compounds. However, the computational bu

safetyarxiv-cs-lg

11 Jun 2026

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning

arXiv:2606.12195v1 Announce Type: new Abstract: Recent progress in foundation models has shifted toward agentic behavior involving multi-step reasoning and tool use. However, open-source efforts large

KinematicRL: A Sim-to-Real Reinforcement Learning Framework For Social Navigation With Kinodynamic Feasibility

arXiv:2606.12042v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) has shown promise for social navigation, yet its real-world deployment remains hindered by a persistent sim-to-real ga

safetyarxiv-cs-ro

Machine-learning-based multipoint optimization of fluidic injection parameters for improving nozzle performance

arXiv:2409.12707v2 Announce Type: replace-cross Abstract: Fluidic injection offers a promising solution to improve the performance of the overexpanded single expansion ramp nozzles (SERNs) during vehi

Mirror Descent Beyond Euclidean Stability: An Exponential Separation in Initialization Sensitivity

arXiv:2606.11431v1 Announce Type: new Abstract: Mirror Descent (MD) extends Gradient Descent (GD) beyond Euclidean geometry and has recently reappeared as a lens for KL-regularized policy optimization

safetyarxiv-cs-lg

Open Materials Generation with Inference-Time Reinforcement Learning

arXiv:2602.00424v2 Announce Type: replace Abstract: Continuous-time generative models for crystalline materials enable inverse materials design by learning to predict stable crystal structures, but in

safetyarxiv-cs-lg

PianoKontext: Expressive Performance Rendering from Deadpan Context

arXiv:2606.12282v1 Announce Type: cross Abstract: Expressive performance rendering (EPR) aims to generate realistic performances constrained on sequences of notes. However, flow matching audio editing

ProHiFlo: Hierarchical Flow Matching with Functional Guidance for De Novo Protein Generation

arXiv:2606.11243v1 Announce Type: cross Abstract: De novo protein generation has transformative potential in therapeutic design, enzyme engineering, and synthetic biology. While diffusion-based and fl

researcharxiv-cs-cl

Redesign Mixture-of-Experts Routers with Manifold Power Iteration

arXiv:2606.12397v1 Announce Type: cross Abstract: Router is the cornerstone component to the Mixture-of-Experts models. Serving as expert proxies, the rows of the router matrix compute their similarit

SheafStain: Sheaf-Theoretic Schrodinger Bridge for Spatially and Biologically Coherent Virtual Staining

model-releasesarxiv-cs-cv

arXiv:2606.11846v1 Announce Type: new Abstract: Current virtual staining approaches offer the potential for time- and cost-efficient biomarker quantification in cancer diagnostics and prognostics. How

SHERPA: Seam-aware Harmonized ERP Adaptation for Open-Domain 360^irc Panorama Generation

arXiv:2606.12213v1 Announce Type: new Abstract: Panoramic imagery is increasingly used in world-generation, games, and simulation, where users may need not only photorealistic scenes but also stylized

researcharxiv-cs-cv

SPADE: Split-and-Delay Embeddings for Autoregressive High-Granularity Calorimeter Simulation

arXiv:2606.11304v1 Announce Type: cross Abstract: We introduce SPADE (SPlit And Delay Embeddings), an autoregressive transformer for sequences whose tokens carry multiple features. Rather than embeddi

Steering Multirobot Behavior via Closed-Loop Affine Activation Editing

arXiv:2606.11489v1 Announce Type: new Abstract: Real-world robots need to adapt their behavior beyond the envelope of their pre-trained policy. Policy finetuning or retraining are options, but they ri

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Time-Series Foundation Model Embeddings for Remaining Useful Life Estimation

model-releasesarxiv-cs-ai

arXiv:2606.11990v1 Announce Type: cross Abstract: Remaining Useful Life (RUL) prediction is essential for industrial predictive maintenance, yet many learning-based approaches rely on extensive featur

TimeRouter: Efficient and Adaptive Routing of Time-Series Foundation Models

model-releasesarxiv-cs-lg

arXiv:2606.11625v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) are increasingly explored as predictive experts within emerging agentic time-series systems. However, TSFMs exhibi

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions

arXiv:2606.11314v1 Announce Type: new Abstract: We introduce TRON, a rendering framework that combines 3D Gaussian ray tracing with neural rendering to enable realistic and controllable rendering of r

applicationsarxiv-cs-cv

ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation

arXiv:2606.12023v1 Announce Type: new Abstract: Vision Transformers (ViTs) have gained significant attention in computer vision and shown strong potential for face recognition (FR). However, their hig

A Source Domain is All You Need: Source-Only Cross-OS Transfer Learning for APT Anomaly Detection via Semantic Alignment and Optimal Transport

arXiv:2606.10216v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are stealthy, multi-stage cyberattacks whose detection is difficult due to scarce labeled traces, severe class imba

A Unified Adaptive Feature Composition Framework for Multi-Task Generalization in Wireless Foundation Models

arXiv:2606.10277v1 Announce Type: new Abstract: Though wireless foundation models (WFMs) have shown strong potential in learning universal channel representations, their adaptation to various downstre

A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

arXiv:2606.11189v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) typically maximizes the likelihood of every token in a demonstrated trajectory. However, an observed token can be non-uni

tutorialsarxiv-cs-ai

Analyzing Training-Free Corruption Detection for Object Detection Datasets

arXiv:2606.10666v1 Announce Type: new Abstract: Annotation errors are widespread in computer vision datasets and can significantly degrade the performance of systems trained on them, particularly in c

applicationsarxiv-cs-cv

AnyMod-LLVE: Low-Light Video Enhancement with Modality-Agnostic Inference

arXiv:2606.11186v1 Announce Type: new Abstract: Low-light video enhancement (LLVE) remains a challenging task due to severe information degradation under low-illumination conditions. Recent multimodal

applicationsarxiv-cs-cv

BiWM: Advancing Open-Source Interactive Video World Models with Bidirectional Autoregression

arXiv:2606.10135v1 Announce Type: cross Abstract: Transitioning bidirectional video diffusion models into an autoregressive paradigm improves the interactivity of video world models, but existing caus

applicationsarxiv-cs-ai

DECSELFMASK: Leveraging Unlabeled Text via Self-Relevance-Guided Masking for Decoder-Only Classification

arXiv:2606.09466v2 Announce Type: replace Abstract: Classification tasks require annotated data, which can often be expensive, time-consuming, or even unfeasible to collect. This is the case of the me

researcharxiv-cs-cl

Deep Slice Interpolation for Reducing Through-Plane Anisotropy and Noise in Head CT

arXiv:2606.09953v1 Announce Type: cross Abstract: Head computed tomography (CT) typically uses sub-millimeter in-plane resolution but 2-5 mm through-plane spacing, creating substantial anisotropy that

Local Ai

Density Field State Space Models: 1-Bit Distillation, Efficient Inference, and Knowledge Organization in Mamba-2

arXiv:2606.10932v1 Announce Type: new Abstract: We present Density Field State Space Models (DF-SSM), a framework for compressing SSMs to a 1-bit scaffold with int8 low-rank correction. Applied to Mam

local-aiarxiv-cs-cl

Don't waste SAM

model-releasesarxiv-cs-cv

arXiv:2606.10696v1 Announce Type: new Abstract: Meta AI has recently released the Segment Anything Model (SAM), which demonstrates exceptional zero-shot image segmentation performance across various t

FlexPath: Learned Semantic Path Priors for Image-Based Planning

arXiv:2606.10167v1 Announce Type: new Abstract: Recent learning-based path planners use neural networks to process visual map representations and approximate heuristics for classical search algorithms

researcharxiv-cs-cv

FOGO: Forgetting-aware Orthogonalization Optimizer

arXiv:2606.10406v1 Announce Type: cross Abstract: We argue that forgetting is not confined to continual learning but is a general optimization phenomenon: during standard training, dominant mini-batch

Globally Localizing Lunar Rover in Pixels via Graph Alignment

arXiv:2606.10602v1 Announce Type: new Abstract: Precise rover localization is a prerequisite for autonomous lunar exploration, yet the absence of Global Navigation Satellite System (GNSS) signals and

LAFP: Preserving Latent Action Structure in Latent Policy Learning via Flow Matching

arXiv:2606.10517v1 Announce Type: new Abstract: Learning high-quality latent actions from large-scale unlabeled videos, coupled with limited real-world interaction data for training an action decoder,

Leveraging Metric Depth for Relative Depth Prediction

arXiv:2606.10628v1 Announce Type: new Abstract: We present our solution to the 2025 SoccerNet Monocular Depth Estimation Competition Challenge. Predicting the relative depth in football scenarios is c

tutorialsarxiv-cs-cv

Next Forcing: Causal World Modeling with Multi-Chunk Prediction

model-releasesarxiv-cs-cv

arXiv:2606.11187v1 Announce Type: new Abstract: Autoregressive video generation has emerged as a powerful paradigm for World Action Models (WAMs). However, existing approaches suffer from slow trainin

One Token per Multimodal Evidence: Latent Memory for Resource-Constrained QA

arXiv:2606.10572v1 Announce Type: new Abstract: External memory effectively grounds large language models (LLMs) and vision-language models (VLMs)-based question answering (QA) in relevant multimodal

Parallel Causal Associative Fields: Gated Sparse Memory for Long-Context Language Modeling

model-releasesarxiv-cs-cl

arXiv:2606.10435v1 Announce Type: cross Abstract: Transformers achieve strong language modeling performance by providing direct token-to-token communication paths, but causal self-attention scales qua

Piper: A Programmable Distributed Training System

model-releasesarxiv-cs-ai

arXiv:2606.11169v1 Announce Type: cross Abstract: Large-scale model training increasingly relies on composing multiple parallelism strategies, such as data, pipeline, and expert parallelism, together

Hardware

Sampling Triangulations and Calabi-Yau Threefolds with Autoregressive GNNs

arXiv:2605.27770v2 Announce Type: cross Abstract: We introduce `dualGNN', an autoregressive message-passing GNN for sampling fine, regular triangulations (FRTs) of convex polytopes. dualGNN operates o

hardwarearxiv-cs-lg

Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS

arXiv:2606.09837v1 Announce Type: cross Abstract: Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the stre

Speech Meets ELF: Audio Conditional Continuous-Target Diffusion for Speech Recognition and Translation

arXiv:2606.10368v1 Announce Type: cross Abstract: Speech-to-text (S2T) systems for recognition (ASR) and translation (S2TT) typically generate discrete text tokens. In contrast, continuous-target lang

Task Robustness via Re-Labelling Vision-Action Robot Data

arXiv:2606.10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize t

safetyarxiv-cs-lg

Local Ai

Tractogram foundation model

arXiv:2606.09893v1 Announce Type: cross Abstract: Diffusion MRI (dMRI) tractography is the only noninvasive approach for mapping white-matter pathways in the living human brain. It represents each bra

local-aiarxiv-cs-ai

A generalizable 3D framework and model for self-supervised learning in medical imaging

arXiv:2501.11755v2 Announce Type: replace-cross Abstract: Current self-supervised learning methods for 3D medical imaging rely on simple pretext formulations and organ- or modality-specific datasets,

researcharxiv-cs-cv

A Systematic Study of Behavioral Cloning for Scientific Data Annotation

arXiv:2606.07568v1 Announce Type: cross Abstract: Scientific data annotation, such as tracking animals in video or proofreading neural reconstructions, remains bottlenecked by the 'last mile' problem:

tutorialsarxiv-cs-ai

A Unifying View of Attention Sinks: Two Algorithms, Two Solutions

arXiv:2606.08105v1 Announce Type: new Abstract: When attention concentrates on a single token, a sink, what is the model actually computing? Attention sinks are ubiquitous in softmax transformers, yet

A Universal Dense Football Event Representation Based on TabTransformer

arXiv:2606.09327v1 Announce Type: cross Abstract: Football event data constitute a rich spatiotemporal source for quantitative analysis of player actions in team sports. These datasets contain heterog

tutorialsarxiv-cs-ai

AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing

arXiv:2606.09811v1 Announce Type: cross Abstract: World-action models have emerged as a promising paradigm for robot manipulation, jointly modeling visual scene dynamics and actions to inject physical

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model

arXiv:2507.08920v4 Announce Type: replace-cross Abstract: We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, e