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Controllable Clothing: Precise Labels and Generation for Virtual Try-On with Latent Diffusion Models

arXiv:2608.05834v1 Announce Type: new Abstract: In this technical report, I present a new method for guiding image generation in the context of Virtual- Try-On (VITON). The proposed method leverages n

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Model Releases

ConWriter: Transition-Constrained Stateful Long-Form Story Generation with Lightweight Neuro-Symbolic Consistency Control

DGX agent

arXiv:2608.05169v1 Announce Type: new Abstract: Long-form story generation requires models to preserve narrative consistency across extended contexts, yet existing prompting-based methods often accumu

model-releasesarxiv-cs-cl

7 Aug 2026

Coordinated Multi-Robot Disassembly for Makespan Optimization of Large-Scale Assemblies

arXiv:2608.05830v1 Announce Type: new Abstract: Multi-robot task and motion planning for disassembly tasks requires robots to operate in confined workspaces while coordinating their motions with other

researcharxiv-cs-ro

CoordRefer: Coordinate-Aware 3D Visual Grounding from Multiview Images

arXiv:2608.05569v1 Announce Type: new Abstract: Multiview image-based 3D visual grounding predicts a coordinate frame to define a coordinate system and then regresses a 3D bounding box for localizatio

safetyarxiv-cs-cv

Counterfactual Analysis via Large Language Models

arXiv:2608.05367v1 Announce Type: new Abstract: Counterfactual analysis aims to predict potential outcomes under hypothetical scenarios, offering valuable insights for decision-making. This paper inve

CourseGraph: Finding overlaps and differences in Computer Science courses across universities

arXiv:2608.05910v1 Announce Type: new Abstract: Student mobility programs such as Erasmus+ enable students to take courses at other universities, broadening their academic and cultural horizons. Howev

CPC-CMS: Cognitive Pairwise Comparison Classification Model Selection Framework for Document-level Sentiment Analysis

arXiv:2507.14022v2 Announce Type: replace Abstract: This study proposes the Cognitive Pairwise Comparison Classification Model Selection (CPC-CMS) framework for document-level sentiment analysis. The

researcharxiv-cs-cl

CREBench: Evaluating Large Language Models in Cryptographic Binary Reverse Engineering

arXiv:2604.03750v2 Announce Type: replace-cross Abstract: Reverse engineering (RE) is central to software security, particularly for cryptographic programs that handle sensitive data and are highly pr

CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search

arXiv:2508.02091v4 Announce Type: replace-cross Abstract: Approximate nearest-neighbor search (ANNS) algorithms have become increasingly critical for recent AI applications, particularly in retrieval-

Cross-Architecture Steering Transfer in Language Models: A Systematic Empirical Study

model-releasesarxiv-cs-cl

arXiv:2608.05164v1 Announce Type: new Abstract: Independently trained large language models may develop shared internal representations of semantic concepts despite architectural differences -- but wh

Hardware

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

arXiv:2512.02551v4 Announce Type: replace-cross Abstract: In this paper, we propose CUDA-L2, a system that combines large language models (LLMs) and reinforcement learning (RL) to automatically optimi

hardwarearxiv-cs-ai

Local Ai

Curia-MAE: Multi-Modal Multi-Anatomy MAE Pre-Training for 3D Medical Image Segmentation

arXiv:2608.05844v1 Announce Type: new Abstract: Radiology foundation models learn transferable representations that can be adapted to new tasks by training only small layers on top of a frozen encoder

local-aiarxiv-cs-cv

D-CLOT: Double Closed Loop Optimal Transport for Unsupervised Action Segmentation

arXiv:2608.05877v1 Announce Type: cross Abstract: Optimal transport (OT) has emerged as an effective framework for unsupervised action segmentation. Yet, in existing OT-based methods, the latent actio

d3LLM: Ultra-Fast Diffusion LLM using Pseudo-Trajectory Distillation

arXiv:2601.07568v3 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) offer capabilities beyond those of autoregressive (AR) LLMs, such as parallel decoding and random-orde

DARAD: Dual Adapters and Ranking-Aware Distillation for Continual Remote Sensing Image-Text Retrieval

arXiv:2608.06059v1 Announce Type: new Abstract: With the rapid growth of Earth observation technologies, remote sensing archives are rapidly expanding, making remote sensing image-text retrieval (RS-I

safetyarxiv-cs-cv

DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization

arXiv:2608.00641v2 Announce Type: replace Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks and optimization

DASH: Divergence-Adaptive Supervision Horizons for On-Policy Self-Distillation of Reasoning Models

arXiv:2608.06243v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models using automatically verifiable outcom

DBLAST: Dependent Block Drafting for Stochastic Speculative Decoding

arXiv:2608.05448v1 Announce Type: new Abstract: Speculative decoding accelerates large language models' inference by using a lightweight drafter to propose multiple future tokens and a target model to

researcharxiv-cs-cl

Decolonizing Linguistic Policies in Automated Speech Recognition: A Framework for Cross-Culturally Competent Speech AI

arXiv:2608.06141v1 Announce Type: new Abstract: This paper focuses on automatic speech recognition (ASR) and ASR-mediated voice interfaces that shape access to public services, healthcare, and educati

safetyarxiv-cs-cl

Decomposed Entailment for Factuality Checking and Hallucination Detection

arXiv:2608.05823v1 Announce Type: new Abstract: The reliability of Large Language Models (LLMs) is often compromised by factual inconsistencies, including hallucinations---cases where generated conten

researcharxiv-cs-cl

Decoupling Perception from Description: Computation-Grounded Representation Alignment between Multivariate Time Series and Language

arXiv:2608.05238v1 Announce Type: new Abstract: Training multimodal models to align time series with language runs into a self-supervision trap. The usual recipe asks an LLM to read a series and write

Deep Generalised Mixed Models: a Novel Neural Network Structure for Analysing Hierarchical Data

arXiv:2608.05930v1 Announce Type: cross Abstract: The experience sampling method (ESM) is a longitudinal research design where participants report their thoughts, emotional states and behaviours multi

DeepForgeSeal: Latent Space-Driven Semi-Fragile Watermarking for Deepfake Detection Using Adversarial Reinforcement Learning

arXiv:2511.04949v2 Announce Type: replace-cross Abstract: Rapid advances in generative AI have led to increasingly realistic deepfakes, posing growing challenges for law enforcement and public trust.

agentsarxiv-cs-ai

Dense-Cast: A lightweight ensemble of deep learning architectures for precipitation nowcasting

arXiv:2608.06082v1 Announce Type: new Abstract: Proper short-term forecasting of precipitation is crucial in disaster management and preparedness. Nonetheless, the variability and nonlinearity of prec

Depth-Guided Video Object Counting in Crowded Scenes

arXiv:2608.06236v1 Announce Type: cross Abstract: Our primary objective is to advance video object counting in crowded scenes, aiming to robustly count all instances of a target category based on give

Design and Evaluation of a Touchscreen-Based Teleoperation Interface for Robotic Manipulators

arXiv:2608.06219v1 Announce Type: new Abstract: Intuitive teleoperation interfaces are crucial for the safe and effective operation of robotic manipulators in challenging environments. In the nuclear

agentsarxiv-cs-ro

Deterministic World Models for Closed-loop Reachability Analysis of End-to-End Vision-based Control

arXiv:2512.08991v3 Announce Type: replace Abstract: End-to-end image controllers that map raw camera frames directly to control actions are increasingly deployed in safety-critical systems. However, f

safetyarxiv-cs-cv

DFM-VLA: Iterative Action Refinement for Robot Manipulation via Discrete Flow Matching

arXiv:2603.26320v4 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models that encode actions using a discrete tokenization scheme have been widely adopted for robotic manipulation

Local Ai

DG-FedReuse: Proxy-Gradient-Gated Cached-Update Reuse with Matched Sparse Uplink Accounting

arXiv:2608.05358v1 Announce Type: new Abstract: Federated learning repeatedly incurs local optimization and model-update transmission. We study DG-FedReuse, a simulator-level mechanism that allows sel

local-aiarxiv-cs-lg

Diff-VF: Training-free High-quality Long Video Generation via Diffusion Model

arXiv:2608.05976v1 Announce Type: new Abstract: Recently, diffusion models have made great progress in video generation. However, most existing video diffusion models are trained with short videos, an

Different Perturbations, Different Mechanisms: Understanding Continued Pre-training for Zero-Shot Dialect Robustness

arXiv:2608.05510v1 Announce Type: new Abstract: Dialectal variation remains a major challenge for multilingual language models. Perturbation-based continued pre-training (CPT) has emerged as a promisi

safetyarxiv-cs-cl

Discrete energy as an exact label-free training objective for finite-element surrogates

arXiv:2608.05437v1 Announce Type: cross Abstract: Supervised training of finite-element (FE) surrogate models requires reference solutions, and each reference solution is obtained by solving the syste

researcharxiv-cs-lg

Disentangling 3D Modeling from Spatial Reasoning

arXiv:2608.05242v1 Announce Type: cross Abstract: In this work, we explore an alternative paradigm for spatial reasoning by explicitly disentangling 3D perception from reasoning, rather than jointly a

agentsarxiv-cs-cv

DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation

arXiv:2608.05683v1 Announce Type: cross Abstract: Cross-modal alignment of visual and textual representations is fundamental to multimodal medical image understanding, yet remains hindered by uncertai

Do Tabular Foundation Models Agree with Themselves?

arXiv:2608.06004v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) are currently the best approach to tabular prediction problems. They are constructed as transformers that approximate t

applicationsarxiv-cs-lg

DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data

arXiv:2608.05375v1 Announce Type: new Abstract: Clinical machine learning (ML) has the potential to support high-stakes medical decision-making, but reliable deployment is often constrained by scarce,

agentsarxiv-cs-ai

Does FLAIR super-resolution erase or hallucinate small white-matter lesions?

arXiv:2608.06311v1 Announce Type: cross Abstract: White matter hyperintensities (WMH), bright regions on Fluid-attenuated Inversion Recovery (FLAIR) scans are associated with cerebrovascular pathology

Does Latent Context Help? A Controlled Evaluation of Inverse Reinforcement Learning in Arctic Shipping

arXiv:2608.06105v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-assisted navigation can help Arctic shipping adapt to rapidly changing sea-ice conditions, but reliable deployment requir

Domain-Grounded Candidate Selection for Agentic Image Editing: A Shadow Removal Case

arXiv:2608.06075v1 Announce Type: cross Abstract: Commercial vision-language models are reshaping computer vision, with visual priors broad enough to rival task-specific systems. This raises a natural

DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph

arXiv:2608.05170v1 Announce Type: cross Abstract: Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accu

DreamGuard: Efficient Runtime Guardrail for LLM Agents via Risk-Aware World Model

arXiv:2608.05695v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly invoke external tools and interact with real-world systems, unsafe actions may cause irreversible cons

DTRNet: Dual Text-Radical Decoding for Handwritten Chinese Text Recognition with Faked Character Detection

arXiv:2608.05848v1 Announce Type: new Abstract: In K-12 educational scenarios, handwritten Chinese text recognition should not only transcribe student writing, but also detect faked characters. Howeve

Dual-Attention and Adversarial Transfer Networks for Sim-to-Real Cross-Orientation Wireless Sensing

arXiv:2608.05664v1 Announce Type: new Abstract: Millimeter-wave human activity recognition suffers significant performance degradation when the user's orientation changes relative to the sensing syste

Dual-Output Multi-Exposure HDR Reconstruction via SDR Fusion and Gain Map Inverse Tone Mapping

arXiv:2608.05626v1 Announce Type: new Abstract: We propose DOME-HDR, a dual-output multi-exposure HDR reconstruction framework that jointly produces a perceptually balanced SDR image and a consistent

Dual-space posterior sampling for Bayesian inference in constrained inverse problems

arXiv:2603.00393v2 Announce Type: replace-cross Abstract: Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniquen

Dynamic Graph Prompting via Topology-Routed Mixed-Curvature Experts

arXiv:2608.06031v1 Announce Type: new Abstract: Dynamic graph prompting freezes a pre-trained temporal backbone and adapts it to label-scarce downstream tasks using lightweight prompts. However, exist

Dynamic Object Masks as Goal Representations for Visual Goal-Conditioned Reinforcement Learning

arXiv:2510.06277v2 Announce Type: replace Abstract: Goal-conditioned reinforcement learning (GCRL) offers a unified way to pursue diverse tasks, yet most existing methods rely on state- or position-ba

Tutorials

Dynamics of Learning under User Choice: Overspecialization and Peer-Model Probing

arXiv:2602.23565v3 Announce Type: replace Abstract: In many economically relevant contexts where machine learning is deployed, multiple platforms obtain data from the same pool of users, each of whom

tutorialsarxiv-cs-lg