All entries

DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference

arXiv:2607.24434v1 Announce Type: cross Abstract: Large Mixture-of-Experts (MoE) language models are attractive for end-device deployment because only a small subset of experts is active per token, bu

Local Ai

DRC-Aid: Design-Rule Correction via Agentic Framework utilizing Inference-Time Large Language Models

DGX agent

arXiv:2607.22761v1 Announce Type: cross Abstract: Resolving Design Rule Violations (DRVs) in layouts entails an iterative loop of geometric edits and verification. We present DRC-Aid, a closed-loop ag

local-aiarxiv-cs-lg

28 Jul 2026

DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces

arXiv:2603.05607v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by sm

DreamStyle3D: Efficient 3D Stylized Asset Generation via Dual-Attention Disentanglement

arXiv:2607.24721v1 Announce Type: new Abstract: With the growth of gaming, animation, and virtual reality industries, the demand for efficient generation of stylized 3D assets is rapidly increasing. H

researcharxiv-cs-cv

DriveDNA: A Large-Scale Multimodal Naturalistic Driving Dataset and Benchmark for Driving Style Identification

arXiv:2607.23822v1 Announce Type: new Abstract: Driving style captures stable, driver-specific patterns in how a vehicle is driven. In naturalistic data, however, this signal is hard to isolate becaus

DRP-FLR: Data-Driven Assessment of Demand Response Potential for Flexible Load Regulation in Smart Grids

arXiv:2607.22590v1 Announce Type: cross Abstract: The rapid growth of AI workloads and renewable energy resources exacerbates supply-demand imbalance in power systems, making traditional load regulati

researcharxiv-cs-lg

DSCH-Loss: A Dynamic Semantic Channel Objective for Deep Semantic Hashing

arXiv:2607.24567v1 Announce Type: new Abstract: Semantic hashing methods for generating short binary hash codes that allow efficient approximate nearest neighbor search in high-dimensional data spaces

DSTFView: Multi-View Cloud-Edge Workload Forecasting with Dual-Input Spatio-Temporal-Frequency Modeling

arXiv:2607.22565v1 Announce Type: new Abstract: With the widespread deployment of edge-side AI inference, edge platforms are increasingly required to support latency-sensitive, highly concurrent, and

DualityCert: Verifier-Gated Language-Model Repair of Broken Duality Claims in Quantum Field Theory

arXiv:2607.23614v1 Announce Type: cross Abstract: We present DualityCert, a symbolic verifier for candidate Seiberg-duality claims in four-dimensional N=1 quiver gauge theories. The verifier evaluates

DuoAD: Leveraging [CLS] Dual Characteristics for Training-Free Few-Shot Anomaly Detection

arXiv:2607.23924v1 Announce Type: cross Abstract: Vision foundation models have enabled strong training-free anomaly detection (AD). However, most existing approaches rely primarily on independent loc

DY-LUT: Depth-Aware YCbCr Lookup Tables for Real-Time Underwater Image Enhancement

model-releasesarxiv-cs-cv

arXiv:2607.22801v1 Announce Type: cross Abstract: Underwater image enhancement is challenged by spatially non-uniform, wavelength-dependent attenuation. Propagation distance and wavelength govern this

DynaCalKV: Key-Value Cache Compression via Head Grouping and Adaptive Rank Allocation

arXiv:2607.24331v1 Announce Type: new Abstract: As the inference phase of Large Language Models (LLMs) requires handling long context windows, the Key-Value (KV) cache initially appears to address thi

Hardware

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training

arXiv:2607.22614v1 Announce Type: new Abstract: RL-based LLM post-training increasingly disaggregates Rollout and Training across separate GPU resources, but static GPU partitioning suffers from sever

hardwarearxiv-cs-ai

E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios

arXiv:2607.23722v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as agents that interact with stateful environments over multiple steps: gathering hidden informat

Earnings25: A Comprehensive 500-Hour Speech Benchmark for Finance

arXiv:2607.23813v1 Announce Type: cross Abstract: We introduce Earnings25, a finance-domain benchmark for evaluating automatic speech recognition (ASR) on English-language earnings calls under realist

Safety

EchoBridge: Long-Tail-Aware ECG-Echocardiography Text Alignment for Echocardiography-Derived Cardiac Findings

arXiv:2607.24553v1 Announce Type: cross Abstract: Standardized echocardiography conclusions provide meaningful supervision for learning ECG representations of echocardiography-derived cardiac findings

safetyarxiv-cs-ai

EditCLEVR: A Paired-Scene Intervention Benchmark for Compositional Faithfulness of Object-Centric Representations

model-releasesarxiv-cs-cv

arXiv:2607.22705v1 Announce Type: new Abstract: Object-centric learning aims to represent scenes as objects whose properties can be reused in new combinations. Existing evaluations usually score segme

EEGForceFusion: Joint Tokenised-Continuous Representation Learning for Subject-Independent Grasp Force Decoding

arXiv:2607.24126v1 Announce Type: cross Abstract: Brain-machine interfaces provide a link between neural activity and external devices, enabling restoration of motor function and advancing human-machi

Tutorials

Effect of User-Prompted Priors on Semi-Automated Cancer Lesion Segmentation in Whole-Body Computed Tomography

arXiv:2607.24210v1 Announce Type: new Abstract: In clinical oncology studies, metastatic cancer is commonly evaluated using 'Response Evaluation Criteria in Solid Tumors' (RECIST), in which the diamet

tutorialsarxiv-cs-cv

Effective Parameters, Real Behavior: Renormalization for Robotics -- From Infinite Electron Mass to Sim-to-Real Gap

arXiv:2607.24079v1 Announce Type: new Abstract: Bridging the sim-to-real gap is a central problem in robotics, and the prevailing approach is to build increasingly accurate simulators. Here, we propos

researcharxiv-cs-ro

Effective Receptive Field Ordering Matters for Infrared Small Target Detection

arXiv:2607.23994v1 Announce Type: new Abstract: In this work, we investigate a previously unexplored architectural dimension for infrared small target detection: the organization of effective receptiv

researcharxiv-cs-cv

Safety

Efficiency Matters in Autonomous Research

arXiv:2607.24647v1 Announce Type: new Abstract: AI-driven autonomous research (AR) systems are becoming increasingly effective across a broad range of tasks. Their performance, however, is still evalu

safetyarxiv-cs-ai

Efficient Learning of Truncated Boolean Product Distributions: Influence to the Rescue

arXiv:2607.22889v1 Announce Type: new Abstract: Learning the natural parameters z in R^n of discrete distributions mu_z from independent samples constrained to a subset S subseteq {0,1}^n is a foundat

Efficient LLM-Generated Shuttling Compilers for Complex Trapped-Ion Architectures

arXiv:2607.24714v1 Announce Type: cross Abstract: Trapped-ion quantum computers rely on shuttling compilers, which cast an input algorithm into a sequence of ion-qubit movements within a given archite

EgoPlay: Event-Triggered Video Editing for Egocentric Streams

arXiv:2607.24560v1 Announce Type: cross Abstract: We introduce EgoPlay, an event-triggered video-to-video editor for egocentric streams, obtained by fine-tuning a pretrained V2V diffusion transformer

Local Ai

Embeddings based Anomaly Detection for Cleaning Global Crop Type Reference Datasets

arXiv:2607.23908v1 Announce Type: new Abstract: High quality reference data remain a critical bottleneck for crop-type mapping at any spatial and temporal scale. Operational systems such as WorldCerea

local-aiarxiv-cs-cv

Embodied GPT-5.1: Evidence of a World Model?

arXiv:2607.23899v1 Announce Type: cross Abstract: This exploratory study examines whether a large multimodal language model, GPT-5.1, can serve as the high-level controller of a physical mobile robot

EmoTrace: An Emotion Trajectory-Centered Framework for Psychological Support Dialogue Generation

arXiv:2607.23648v1 Announce Type: new Abstract: Using large language models (LLMs) to assist psychological counseling is an important task in the field of natural language processing. The construction

researcharxiv-cs-cl

Hardware

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG

arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr

hardwarearxiv-cs-cv

Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection

arXiv:2512.07246v2 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent s

researcharxiv-cs-cl

Safety

Epistemic Norms for AI Safety and Alignment Research

arXiv:2607.24243v1 Announce Type: new Abstract: Mainstream AI research emphasises capability growth and tolerates low failure rates when average-case performance is high. AI safety and alignment resea

safetyarxiv-cs-ai

ERUnderstand: Evaluating Vision-Language Models on Structured ER Diagrams

arXiv:2607.24707v1 Announce Type: new Abstract: Entity-Relationship Diagrams (ERDs) are central to conceptual database design, yet they are typically available only as rendered images rather than mach

Local Ai

Escaping the Euclidean Void: Manifold-Informed Flow Matching for Sequential Recommendation

arXiv:2607.23762v1 Announce Type: cross Abstract: Conventional recommenders capture users' preferences by optimizing observed user-item relations, whereas continuous generative recommendation addition

local-aiarxiv-cs-ai

ESF-Bench: Benchmarking Challenging Slot-Filling Scenarios for Real-World Enterprise Applications

arXiv:2607.23326v1 Announce Type: new Abstract: The rapid rise of large language models (LLMs) has driven transformative adoption across enterprises. However, deploying these models in real-world sett

ESRVS: Extreme Semi-Supervised Retinal Vessel Segmentation with a Single Annotated Image

arXiv:2607.24453v1 Announce Type: cross Abstract: Learning from minimal human supervision is a long-standing goal in medical image analysis, where dense expert annotations are costly. We study retinal

Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests

arXiv:2607.22883v1 Announce Type: cross Abstract: While Large Language Models (LLMs) show great promise for automating unit test generation, recent studies suggest that the quality of generated tests

Evaluating Fuzz Testing for Reinforcement Learning Agents

arXiv:2607.24577v1 Announce Type: new Abstract: Reinforcement Learning (RL) agents are increasingly deployed in safety-critical domains such as robotics, autonomous driving, and drone control, where u

Evaluating Large Language Models for Symbolic Security Protocol Analysis

arXiv:2607.20712v1 Announce Type: cross Abstract: Security protocol verification relies on formal tools such as ProVerif and OFMC. This study evaluates whether Large Language Models (LLMs) can perform

Evaluating LLMs as Interpretable Controllers for Dynamical Systems

arXiv:2607.22609v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for decision-making and reasoning tasks, yet their potential as controllers for physical systems rema

Evaluating RAG for French immigration law: a benchmark and baseline study

arXiv:2607.24449v1 Announce Type: cross Abstract: International recruitment in France requires navigating a layered legal framework absent from existing legal AI benchmarks. We present a publicly avai

Applications

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

arXiv:2607.24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to under

applicationsarxiv-cs-ai

Evaluating the Impact of Reviewer Guideline Design on LLM-Based Automated Peer Review

arXiv:2607.22553v1 Announce Type: cross Abstract: Peer review is an essential process in scientific research, yet the growing workload has made its automation increasingly necessary. In this study, we

Evaluation of Blood Vessel Segmentation Methods on Hard-to-Detect Vascular Structures

model-releasesarxiv-cs-cv

arXiv:2406.13128v2 Announce Type: replace Abstract: Due to the intricate structure of vascular trees, minor segmentation errors can significantly alter connectivity patterns and increase variability i

Event Driven Clustering Algorithm

arXiv:2602.00115v2 Announce Type: replace Abstract: This paper introduces a novel asynchronous, event-driven algorithm for real-time detection of small event clusters in event camera data. Similar to

researcharxiv-cs-cv

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

arXiv:2607.22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models traine

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting

arXiv:2607.24218v1 Announce Type: cross Abstract: Federated learning has emerged as a promising paradigm for spatio-temporal forecasting (STF), enabling collaborative model training without sharing ra

Applications

Everything you need to know about Kimi K3 with @Kimi_Moonshot and @togethercompute team. If you're looking into evaling and building with Ki…

applicationstogether-ai--x

Everything you need to know about Kimi K3 with @Kimi_Moonshot and @togethercompute team. If you're looking into evaling and building with Kimi K3 I would not miss this one! Kimi K3 has everyone’s atte

Agents

EviBack: Search-Agent Reinforcement Learning via Evidence-Constrained Teacher Backoff

arXiv:2607.23955v1 Announce Type: new Abstract: Reinforcement learning enables Agentic RAG systems to learn multi-turn search from verifiable outcome rewards, but all- zero rollout groups provide no c

agentsarxiv-cs-ai