Search: “pretraining”

A Theory of Conditional Collapse under Low-Rank Weight-Space Ablations: I. The Single-Block Theory and Synthetic Validation

arXiv:2608.03620v1 Announce Type: cross Abstract: Activation patching and weight-space ablation both claim a component is causally responsible for a behavior, yet they act on different objects: one fo

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Tutorials

Agogic: Performance-Timed Music Tokens for LLM-Native Text-to-Symbolic-Music Generation

DGX agent

arXiv:2608.03999v1 Announce Type: cross Abstract: Text-to-music language models begin with a choice usually made by default: how to tokenize music. Normally entangled with backbone, data, and recipe,

tutorialsarxiv-cs-cl

5 Aug 2026

ANCHOR-RE: An Agentic Neuro-Symbolic Framework for Grounded Biomedical Relation Extraction

arXiv:2608.03154v1 Announce Type: new Abstract: Biomedical relation extraction (BioRE) extracts structured knowledge from biomedical literature for applications such as knowledge base construction and

CADET: Physics-Grounded Causal Auditing and Training-Free Deconfounding of End-to-End Driving Planners

model-releasesarxiv-cs-ai

arXiv:2606.14438v3 Announce Type: replace-cross Abstract: End-to-end (E2E) autonomous-driving planners trained by imitation are prone to statistical shortcuts: they associate scene elements that merel

Local Ai

CIGTSurv: Clinical Information Guided Tri-modal Survival Prediction with Local Prototype Association and Global Feature Alignment

arXiv:2608.03247v1 Announce Type: cross Abstract: Multimodal learning has significantly advanced survival prediction by integrating pathology images with genomic data. However, clinical information, d

local-aiarxiv-cs-cl

Decoupling Generation and Selection for Budget-Constrained Faithful Summarization

arXiv:2608.03655v1 Announce Type: cross Abstract: Abstractive summarization models remain vulnerable to factual inconsistency, redundancy, and weak length control. We propose a modular generation-and-

DiverseDiT++: Quantifying, Analyzing, and Promoting Representation Diversity in Diffusion Transformers

arXiv:2608.03082v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled remarkable progress in visual synthesis, benefiting from their superior scalability. To fa

safetyarxiv-cs-cv

EditFlow3D: Automated Local Editing of 3D Assets with Trajectory Preservation

arXiv:2608.03179v1 Announce Type: new Abstract: Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple ye

Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems

arXiv:2608.02806v1 Announce Type: cross Abstract: By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve roa

safetyarxiv-cs-cv

Hear to See: Discerning Stateful Listening for Audio-Visual Instance Segmentation

arXiv:2608.03264v1 Announce Type: cross Abstract: Audio-visual instance segmentation (AVIS) requires accurately identifying and tracking individual sounding objects with pixel-level masks. Existing me

HomoEnsNER: Does Language Alignment Outperform Architectural Complexity in Gujarati Named Entity Recognition?

arXiv:2608.03105v1 Announce Type: new Abstract: Named Entity Recognition (NER) for Gujarati remains underexplored, hindered by the absence of capitalization cues, rich morphology, lexical ambiguity, a

safetyarxiv-cs-cl

LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models

arXiv:2608.03457v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dL

Low-Dimensional High-Leverage Subspace Optimization: Beyond Full-Parameter Coupled Training for Neural Network Quantization

arXiv:2608.03919v1 Announce Type: new Abstract: Low-bit quantization suffers severe accuracy degradation on compact networks, rooted in the dominant full-parameter coupled training paradigm that ignor

M-GATE: Multilingual Grammar, Accuracy in Translation, and Efficiency Benchmark for Large Language Models

arXiv:2608.03803v1 Announce Type: new Abstract: Multilingual language models are deployed across a hundred or more languages, yet most benchmarks test whether a model can perform a task _in_ a languag

Maglev: Sliding Recurrent Memory

model-releasesarxiv-cs-lg

arXiv:2608.02870v1 Announce Type: new Abstract: We introduce ours{}, a recurrent Transformer architecture with fixed-size memory that generalizes sliding-window attention while remaining parallelizabl

MDLMPE: Distribution Aware Positional Encoding for Masked Diffusion Language Models

arXiv:2608.03769v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) enable parallel generation and bidirectional context modeling, but their positional context differs fundament

Predictive Enhancement Calibration for Latent Breast MRI Virtual Contrast Enhancement

arXiv:2608.03612v1 Announce Type: cross Abstract: Virtual contrast enhancement (VCE) synthesizes enhanced breast MR images from pre-contrast acquisitions. Modern latent generators offer strong image p

Applications

PRISM: Powerful Time Series to Image (TS2I) Representations for Multivariate Anomaly Detection

arXiv:2608.03926v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) underpins applications in predictive maintenance, finance, and cloud computing, however performance remains sensi

applicationsarxiv-cs-ai

ScoreField: Neural Inverse Scattering with Score-Based Generative Priors

arXiv:2608.02937v1 Announce Type: cross Abstract: Designing an effective electromagnetic inverse-scattering solver requires faithful enforcement of nonlinear full-wave physics together with an express

researcharxiv-cs-lg

Sedentary Behavior Classification for Wearable Sensors with a CNN-BiLSTM Model

arXiv:2608.02946v1 Announce Type: new Abstract: Accurate detection of sedentary behavior is important for studying health risks related to prolonged sitting, but posture-based classification remains c

researcharxiv-cs-lg

Standalone DINOv3 for Training-Free Open-Vocabulary Semantic Segmentation in Remote Sensing

arXiv:2608.03023v1 Announce Type: cross Abstract: Remote sensing semantic segmentation is hindered by costly pixel-level annotations, motivating training-free open-vocabulary methods. Recently, the re

StereoVGGT: A Training-Free Visual Geometry Transformer for Stereo Vision

arXiv:2603.29368v2 Announce Type: replace Abstract: Driven by the advancement of 3D devices, stereo vision tasks including stereo matching and stereo conversion have emerged as a critical research fro

SUV: Future Scene Understanding as Video Generation for End-to-End Driving

arXiv:2608.03084v1 Announce Type: new Abstract: End-to-end driving requires a coherent understanding of future scenes, yet existing methods model these scenes using task-specific heads and output form

UniGD: A Unified Generative-Discriminative Framework for Industrial Retrieval

arXiv:2608.03150v1 Announce Type: new Abstract: Generative retrieval (GR) is a promising paradigm for industrial search advertising, yet its deployment is constrained by strict relevance and latency r

A General-Purpose VLM Can Teach an Astronomy Foundation Model to Better Recognize Galaxy Morphology

arXiv:2608.02300v1 Announce Type: new Abstract: Existing astronomy foundation models provide strong galaxy representations, but adapting them to new survey conditions and survey-specific morphology re

ABRA: Teleporting Fine-Tuned Knowledge Across Domains for Open-Vocabulary Object Detection

arXiv:2603.12409v2 Announce Type: replace Abstract: Although recent Open-Vocabulary Object Detection architectures, such as Grounding DINO, demonstrate strong zero-shot capabilities, their performance

Artificial Intelligence for the Characterization of Particles and Fibers by Optical Microscopy

arXiv:2608.00361v1 Announce Type: new Abstract: Optical microscopy of particle and fiber dispersions involves interpreting subtle visual cues influenced by specimen morphology, chemical composition, m

AttnLink: Turning Attention into Schema Links for Text-to-SQL

arXiv:2608.00693v1 Announce Type: new Abstract: Schema linking is a critical component of Text-to-SQL systems, but existing approaches often trade off contextual modeling capacity, score-based control

Automatic Annotation of Ancient Greek Vowel Length

arXiv:2608.01935v1 Announce Type: new Abstract: Prior work in Ancient Greek NLP relies on corpora that do not disambiguate the phonemic vowel length of alpha, iota, and ypsilon, together known as the

Local Ai

CDG-MAE: Cross-view Masked Modeling using Diffusion Generated Views

arXiv:2506.18164v2 Announce Type: replace Abstract: Cross-view masked autoencoding has emerged as a powerful pretext task for learning dense correspondences, which are essential for applications such

local-aiarxiv-cs-cv

ChaosProbe: A Neurochaotic Lens on Frozen Transformer Input-Embedding Spaces

model-releasesarxiv-cs-lg

arXiv:2608.01968v1 Announce Type: new Abstract: Transformer models are most often understood through what they do: their benchmark performance, generation quality, or behavior on downstream tasks. Yet

CopyCat: Improving Fine-Grained Subject Consistency in Subject-to-Image Models within Seconds

arXiv:2608.00674v1 Announce Type: new Abstract: Recent subject-to-image models have achieved impressive progress in personalized image generation, yet they still struggle to preserve fine-grained subj

CORTIVA: Candidate-Score Fusion of Complementary Visual Teachers for EEG- and MEG-to-Image Retrieval

arXiv:2608.01355v1 Announce Type: new Abstract: Decoding visual experience from non-invasive brain activity is central to neuroscience and brain-computer interfaces. Functional magnetic resonance imag

Developing Combined Manipulation and Locomotion Skills with Interaction Representation and Skill Composition

arXiv:2608.00208v1 Announce Type: new Abstract: This paper addresses how to enable a humanoid robot to learn motion policies based on developmental principles and combine policies to create more sophi

safetyarxiv-cs-ro

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models

arXiv:2608.01263v1 Announce Type: new Abstract: On-policy distillation (OPD) samples trajectories from the current student policy and minimizes token-level divergence between student and teacher next-

safetyarxiv-cs-lg

Driver2Map: Imitating Human Driving for Online High-Definition Map Construction

arXiv:2608.01338v1 Announce Type: new Abstract: High-definition (HD) maps are essential for autonomous driving systems. In constructing such maps, onboard multi-view camera images, standard-definition

safetyarxiv-cs-cv

Applications

DynamicWAM: Dual-Path Motion Conditioning for World-Action Models in Dynamic Manipulation

arXiv:2608.00793v1 Announce Type: new Abstract: Dynamic manipulation requires robots to infer target motion and respond promptly, yet existing World-Action Models (WAMs) typically condition only on th

applicationsarxiv-cs-ro

Event ActivityNet: A Large-Scale Simulated-Event Benchmark for Untrimmed Action Understanding

arXiv:2608.01948v1 Announce Type: new Abstract: Long-horizon event-based action understanding remains underexplored because existing datasets largely comprise short, trimmed clips, while collecting na

Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models

arXiv:2604.01622v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) enable parallel, non-autoregressive text generation, yet existing DLM mixture-of-experts (MoE) models inherit

safetyarxiv-cs-cl

Fast and Accurate Quotation Attribution in Literary Texts

arXiv:2608.02359v1 Announce Type: new Abstract: Attributing quotations to their speakers in literary texts remains an open challenge. Standard methods, which independently predict a speaker mention fo

Foveated Probes Recover Localized Binding Information in Vision Foundation Models

arXiv:2608.00726v1 Announce Type: new Abstract: Frozen vision foundation models are commonly evaluated through a single global image embedding, but this interface can conflate missing information with

Local Ai

FreqAnchorAD: Language-Free Zero-Shot Anomaly Detection via Frequency-Deviation Anchoring

arXiv:2608.00695v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to detect anomalies and localize defective regions in unseen target domains without target training data. Recent

local-aiarxiv-cs-cv

From Chains to Trees: Parent-Conditioned Drafting for Semi-Autoregressive Speculative Decoding

arXiv:2608.02123v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference only when drafted continuations survive target-model verification. Semi-autoregressive drafters such as D

researcharxiv-cs-cl

Fused Bayesian Flow Networks for Dual-Target Molecular Design

model-releasesarxiv-cs-lg

arXiv:2608.01007v1 Announce Type: new Abstract: Dual-target drug design aims to generate 3D molecules that can simultaneously interact with two target proteins, offering a promising route for discover

Tutorials

Gecko: Fast Private Inference via Secure Public Encoder Offloading

arXiv:2608.02378v1 Announce Type: new Abstract: Private inference protects both user inputs and server models during neural network inference, but existing solutions remain too slow for practical depl

tutorialsarxiv-cs-lg

Geometry-Guided Layerwise FFN Width Allocation in Transformers

arXiv:2608.02064v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) account for a large fraction of Transformer parameters, yet their hidden width is usually constant across depth. We ask w

researcharxiv-cs-cl

Grounded Semantic Re-Binding for Robust Instruction Generalization in Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.02497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models excel in robotic manipulation but suffer catastrophic performance drops when canonical instructions are simply parap

Inference-Time Policy Alignment for Fair Reinforcement Learning

arXiv:2608.00175v1 Announce Type: new Abstract: Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these

safetyarxiv-cs-lg