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DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks

model-releasesarxiv-cs-lg

arXiv:2607.07946v1 Announce Type: cross Abstract: DeepSWE is a benchmark of 113 original, long-horizon software engineering tasks for evaluating coding agents. Most public agentic coding benchmarks fo

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DeltaDeno: Zero-Shot Anomaly Generation via Delta-Denoising Attribution

DGX agent

arXiv:2511.16920v2 Announce Type: replace Abstract: Anomaly generation is often framed as few-shot fine-tuning with anomalous samples, which contradicts the scarcity that motivates generation and tend

safetyarxiv-cs-cv

10 Jul 2026

DeltaV: Thinking with Visual State Updates in Unified Large Multimodal Models

arXiv:2607.08434v1 Announce Type: new Abstract: Current Unified Large Multimodal Models (ULMMs) support interleaved multimodal reasoning through textual reasoning and intermediate visual states, but t

Design optimization and robustness analysis of rigid-link flapping mechanisms

arXiv:2503.21204v3 Announce Type: replace Abstract: Rigid link flapping mechanisms remain the most practical choice for flapping wing micro-aerial vehicles (MAVs) to carry useful payloads and onboard

applicationsarxiv-cs-ro

Detecting Ladder Logic Bombs in IEC 61131-3 PLC Programs using ESBMC-PLC+: A Formal Verification Approach with Trigger Synthesis

arXiv:2607.08417v1 Announce Type: new Abstract: A Ladder Logic Bomb (LLB) is malicious control logic in a Programmable Logic Controller (PLC) program that lies dormant until a trigger activates a payl

safetyarxiv-cs-cl

DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.08751v1 Announce Type: new Abstract: Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across di

Diagnosing Corruption-Induced Reliability Failures in Vision-Language Models

arXiv:2511.19032v2 Announce Type: replace Abstract: Visual corruptions can change vision--language model (VLM) behavior in ways that top-1 accuracy does not capture. A model may keep the same answer w

safetyarxiv-cs-cv

Diagnosing Shape-Prior Shortcuts in Long-Range Single-Shot Fringe Projection Profilometry

model-releasesarxiv-cs-lg

arXiv:2606.17093v2 Announce Type: replace Abstract: Learning-based single-shot fringe projection profilometry (FPP) has been studied almost entirely at close range, and the networks used are evaluated

Diarization-Guided Qwen-ASR Adaptation for Multilingual Two-Speaker Conversational Speech

arXiv:2607.08208v1 Announce Type: new Abstract: This paper describes our self-designed system for Task 1 of the MLC-SLM 2026 Challenge for multilingual two-speaker conversational speech. The system co

Different Teachers, Different Capabilities: Sub-1B On-Device Distillation for Structured Text Enrichment

model-releasesarxiv-cs-ai

arXiv:2607.08268v1 Announce Type: new Abstract: High-volume structured extraction pays a large model's latency on every item, so distilling the task into a small on-device model is attractive: compara

Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph

arXiv:2607.08746v1 Announce Type: cross Abstract: While UMAP is widely used for exploring high-dimensional data, typical workflows focus on its lower-dimensional embedding, largely overlooking the ric

Distributed Sketching on Data Partitions for OLS Regression

arXiv:2607.07888v1 Announce Type: new Abstract: This paper studies distributed sketching for ordinary least squares (OLS) regression, an approach that distributes small sketches of a large data set ov

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation

arXiv:2607.07767v1 Announce Type: cross Abstract: Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametri

applicationsarxiv-cs-lg

Dive Into the Implicit Biases of Low-rank Vision-language Alignment

arXiv:2607.08194v1 Announce Type: new Abstract: Vision-language alignment, the stage that bridges pretrained vision encoders and large language models, is widely treated as a form of pretraining requi

DKDNet: Dual Knowledge and Data-Driven Network for Cross-Domain Automatic Modulation Classification

arXiv:2607.08031v1 Announce Type: cross Abstract: The dynamics of communication environments induce significant distribution shifts across domains, challenging the generalization of deep learning-base

Do Egocentric Video-Language Models Capture Both Hand- and Object-Centric Cues?

arXiv:2607.08514v1 Announce Type: new Abstract: Hand-object interaction (HOI) recognition requires capturing both hand manipulations and object transformations. However, existing video-language models

researcharxiv-cs-cv

Do Transformations Reveal the Truth? Generative Residual Learning for Generalized AI-Generated Image Detection

arXiv:2607.08674v1 Announce Type: new Abstract: The rapid advancement of generative AI has enabled the creation of highly realistic deepfake media, posing significant threats, including misinformation

Do You Need a Frontier Model as a Citation Verifier? Benchmarking Rubric LLMs for Deep-Research Source Attribution

arXiv:2607.08700v1 Announce Type: new Abstract: Reinforcement learning increasingly relies on an LLM judge to score each rubric criterion, and that judge acts as the reward model during training. Befo

DocMaster: A Hierarchical Structure-Aware System for Document Analysis

arXiv:2607.08539v1 Announce Type: cross Abstract: Leveraging large language models (LLMs) to analyze complex documents -- such as academic papers, technical manuals, and financial reports -- has emerg

DominoTree: Conditional Tree-Structured Drafting with Domino for Speculative Decoding

arXiv:2607.08642v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by drafting several tokens and verifying them in parallel. Block-diffusion drafters such as DFlash produc

Douglas-Rachford Splitting for Group-Sparse Feedback Linear-Quadratic Control

arXiv:2507.19895v4 Announce Type: replace-cross Abstract: In this paper, we study the distributed linear quadratic problem with fixed communication topology (DFT-LQ) and the sparse feedback linear qua

DR-Arena: an Automated Evaluation Framework for Deep Research Agents

arXiv:2601.10504v2 Announce Type: replace Abstract: As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, rel

safetyarxiv-cs-cl

DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation

arXiv:2607.07817v1 Announce Type: cross Abstract: We present DreamCharacter-1, a lightweight post-adaptation framework that calibrates pretrained 3D foundation models toward high-fidelity, production-

applicationsarxiv-cs-ai

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607.08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time. Static embeddings an

Dropping Just a Handful of Preferences Can Change Top Large Language Model Rankings

arXiv:2508.11847v4 Announce Type: replace-cross Abstract: We propose a method for evaluating the robustness of widely used LLM ranking systems -- variants of a Bradley--Terry model -- to dropping a wo

DrugGen 2: A disease-aware language model for enhancing drug discovery

arXiv:2607.08404v1 Announce Type: cross Abstract: Current computational approaches for drug design typically focus on generating molecules conditioned on specific targets or general molecular properti

Dual-Correlation Hypergraph Network for Unaligned RGBT Video Object Detection and A Large-scale Benchmark

arXiv:2607.08191v1 Announce Type: new Abstract: RGB-Thermal (RGBT) Video Object Detection (VOD) has gained significant traction due to its ability to overcome the limitations of conventional RGB-based

Dual-Difficulty Curriculum Learning for Direct Preference Optimization

arXiv:2504.07856v4 Announce Type: replace Abstract: Curriculum learning enhances Direct Preference Optimization (DPO) for aligning Large Language Models (LLMs), yet existing methods rely on a one-dime

Dynamics of Gradient Descent with Large Step Size Near a Manifold of Flat Minima

arXiv:2607.08380v1 Announce Type: new Abstract: An important quantity in the theory of gradient descent (GD) is the sharpness, defined as the largest eigenvalue of the objective Hessian. Classical ana

Early to Share, Late to Save: Synchronisation-Driven Communication Gating in Bandwidth-Constrained Cooperative VLN

arXiv:2607.08504v1 Announce Type: cross Abstract: Most cooperative Vision-Language Navigation (VLN) methods assume unlimited communication, not considering real-world applications where bandwidth is r

safetyarxiv-cs-ro

Echoes: A semantically-aligned music deepfake detection dataset

arXiv:2603.23667v2 Announce Type: replace-cross Abstract: We introduce Echoes, a new dataset for music deepfake detection designed for training and benchmarking detectors under realistic and provider-

Echoes Across Vietnam's Highlands, Delta, and Coast: A Multilingual Corpus for Cham, Khmer, and Tay-Nung

arXiv:2607.08362v1 Announce Type: new Abstract: Vietnam's ethnic minority languages are almost absent from the field of Natural Language Processing (NLP), and the challenge goes beyond data scarcity:

EdgeRefine: Privacy-Utility Balance for Graphs via Jaccard Sampling under Edge Differential Privacy

arXiv:2607.08659v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have shown considerable success in learning from graph-structured data, but their use in privacy-sensitive areas remains di

Effective Gaussian Management for High-fidelity Scene Reconstruction

arXiv:2509.12742v4 Announce Type: replace Abstract: This paper proposes an effective Gaussian management framework for high-fidelity scene reconstruction of both appearance and geometry. Unlike recent

researcharxiv-cs-cv

Efficient Partitioning Method of Large-Scale Public Safety Spatio-Temporal Data based on Information Loss Constraints

arXiv:2306.12857v3 Announce Type: replace Abstract: The storage, management, and application of massive spatio-temporal data are widely used in practical scenarios, including public safety. However, d

safetyarxiv-cs-lg

Efficient Safety Alignment of Language Models via Latent Personality Traits

arXiv:2607.07918v1 Announce Type: cross Abstract: Current safety methods for large language models are known to be vulnerable to adversarial attacks, motivating research into robust alternatives. Late

EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data

arXiv:2607.08436v1 Announce Type: cross Abstract: Egocentric human data offers scalable supervision for robot manipulation. However, behavior cloning entangles transferable content like objects, scene

Eigenvalue Calibration for Semantic Embeddings of Large Language Models

arXiv:2607.08377v1 Announce Type: new Abstract: Uncertainty quantification is central to the reliable deployment of large language models (LLMs), and eigenvalues of semantic embeddings have recently e

applicationsarxiv-cs-lg

Elastic3D: Controllable Stereo Video Conversion with Guided Latent Decoding

arXiv:2512.14236v2 Announce Type: replace Abstract: The growing demand for immersive 3D content calls for automated monocular-to-stereo video conversion. We present Elastic3D, a controllable, direct e

applicationsarxiv-cs-cv

Tutorials

Enhancing In-context Panoramic Generation via Geometric-aware Pretraining

arXiv:2607.08765v1 Announce Type: new Abstract: In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream t

tutorialsarxiv-cs-cv

Enhancing the KidSat Model: Integrating Geographical Encoding and Data Quality Assessment for Childhood Poverty Prediction

arXiv:2607.08281v1 Announce Type: new Abstract: Accurate poverty mapping using satellite imagery is often hindered by (i) noisy and sparse survey-derived supervision, (ii) image quality issues such as

researcharxiv-cs-cv

Ensemble Diversity Optimization for Subjective Supervision

arXiv:2607.08493v1 Announce Type: cross Abstract: Subjective NLP tasks often exhibit systematic annotator disagreement, requiring models that represent uncertainty rather than collapse it. We introduc

safetyarxiv-cs-cl

Equivariant Quantum Clustering with Differential Privacy: Parameter-Efficient Privacy-Preserving Analysis Across Heterogeneous Sensitive Datasets

arXiv:2607.08092v1 Announce Type: cross Abstract: Privacy-preserving clustering is critical for analyzing sensitive data in healthcare, cybersecurity, and enterprise applications, where maintaining da

Evaluating the Effect of Frame Rate in Sequence-Based Classification of Autism-Related Self-Stimulatory Hand Idiosyncrasies

arXiv:2607.07957v1 Announce Type: new Abstract: Autism spectrum disorder (ASD) affects over 75 million individuals worldwide, yet scalable computational methods for remote behavioral screening remain

Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5

model-releasesarxiv-cs-lg

arXiv:2607.07951v1 Announce Type: new Abstract: Wildfire smoke events produce extreme PM_{2.5} concentrations that pose severe public health risks, yet forecasting rare, hazardous-level spikes remains

Hardware

EVIS: A Physics-Grounded Event Camera Plugin for NVIDIA Isaac Sim

arXiv:2607.08098v1 Announce Type: new Abstract: Event cameras offer microsecond temporal resolution, low latency, and high dynamic range, making them attractive for robotics. However, labeled event-ca

hardwarearxiv-cs-cv

Local Ai

Explaining Near-Zero Hessian Eigenvalues Through Approximate Symmetries in Neural Networks

arXiv:2607.07845v1 Announce Type: new Abstract: The Hessian of the training loss governs the local geometry of the loss landscape, yet despite existing explanations for its largest eigenvalues, the or

local-aiarxiv-cs-lg

Expressivity and Statistical Trade-offs in Diffusion Policy Learning

arXiv:2607.07967v1 Announce Type: cross Abstract: Diffusion-based policies have recently emerged as powerful policy parameterizations for reinforcement learning, representing state-conditioned action

safetyarxiv-cs-lg