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arXiv:2608.31128v1 Announce Type: new Abstract: Large language models (LLMs) offer promising clinical decision support but remain vulnerable to hallucinated facts, unsupported recommendations, and cit

agentsarxiv-cs-cl

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DICS: Exploring Data Intrinsic Consistency for Visual Instruction Selection

DGX agent

arXiv:2608.30209v1 Announce Type: new Abstract: Visual instruction tuning is crucial for advancing the vision-language alignment and instruction-following capabilities of Vision-Language Models (VLMs)

safetyarxiv-cs-cv

1 Sept 2026

Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environments

arXiv:2608.29907v1 Announce Type: new Abstract: Future wireless systems are expected to transform the surrounding space from a passive propagation medium into a smart electromagnetic environment, wher

researcharxiv-cs-lg

Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding

arXiv:2505.16990v3 Announce Type: replace Abstract: In this work, we propose Dimple, the first Discrete Diffusion Multimodal Large Language Model (DMLLM). We observe that training with a purely discre

Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice

arXiv:2507.05512v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for code generation, making reliable identification of machine-generated code important for

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing

arXiv:2607.02290v2 Announce Type: replace Abstract: Recent image generation and editing models can produce visually appealing natural images, yet they remain unreliable when the target image is a know

Distributional Validity and Calibration of a Korean Synthetic Persona Panel for Digital and AI Service Use: A Secondary-Data Validation Against the Korea Media Panel Survey

arXiv:2608.28615v1 Announce Type: cross Abstract: Synthetic personas based on large language models (LLMs) are increasingly proposed as substitutes for human survey respondents, yet systematic validat

Tutorials

Do Language Models Reason Across Languages?

arXiv:2601.06644v2 Announce Type: replace-cross Abstract: The real-world information sources are inherently multilingual, which naturally raises a question about whether language models can synthesize

tutorialsarxiv-cs-ai

Do Small Models Use the Law You Give Them? Measuring Context Use on a Bilingual Bangladesh Legal Benchmark

arXiv:2608.30327v1 Announce Type: new Abstract: Fine-tuning can improve legal question-answering accuracy without improving how models use law supplied in context. We study this distinction in bilingu

Does Latent Planning Survive Point Clouds? Action-Conditioned JEPA World Models for Geometric Observations

arXiv:2608.29434v1 Announce Type: cross Abstract: JEPA world models make latent-space planning a practical route to control, but they are built almost exclusively on images. Whether latent prediction

DreamX-Creator: Democratizing Native Audio-Video Generation at 2K Resolution

arXiv:2608.31106v1 Announce Type: new Abstract: Recent video generators often omit audio or synthesize it in a separate stage, limiting reciprocal modeling of visual dynamics and acoustic events. We p

DriftingVLA: Native One-Step Vision-Language-Action Generation via Per-Dimension Temporal Drifting

arXiv:2608.29749v1 Announce Type: new Abstract: Conventional flow-based vision-language-action (VLA) models support expressive continuous action generation but rely on multi-step refinement to produce

safetyarxiv-cs-ro

Effective Graph and Rank-based Contextual Embeddings for Textual and Multimedia Data

arXiv:2608.29001v1 Announce Type: cross Abstract: In a data-driven world, efficiently organizing and mapping relationships between objects is crucial. Graphs are powerful tools for modeling these conn

Efficient and High-Quality Depth Estimation via Pixel-Space Diffusion with Linear Attention

arXiv:2608.30129v1 Announce Type: new Abstract: This work presents extbf{Lapis}, a extbf{l}inear-extbf{a}ttention-based extbf{pi}xel-extbf{s}pace generative framework that achieves efficient and high-

Efficient JPEG Restoration in the Wavelet Domain via Mean Flows

arXiv:2608.28730v1 Announce Type: cross Abstract: Latest JPEG restoration systems achieve strong quality with large models, yet often remain too slow and expensive for efficient on-device deployment.

EMERGE-Policy: A Robot Mind Emerges Beyond a Single Policy

model-releasesarxiv-cs-ro

arXiv:2608.29896v1 Announce Type: new Abstract: A robot's effective ``mind'' need not reside in a single policy. It can emerge when specialized components perceive, reason, predict, act, verify, and r

En-ViMedNER: An English-Vietnamese Parallel Biomedical Corpus with UMLS Semantic Type Annotations

arXiv:2608.29890v1 Announce Type: new Abstract: Biomedical Named Entity Recognition (NER) is fundamental to healthcare AI applications, including clinical decision support and medical information extr

Enabling Proactive Spoken Turns via a Generalized Style-Aware Full-Duplex Framework

arXiv:2608.28630v1 Announce Type: cross Abstract: Compared with half-duplex dialogue systems where the system waits for user turn completion before it responds, natural full-duplex dialogue systems re

applicationsarxiv-cs-ai

End-to-End Neural Shrinkage of Indefinite Pairwise Correlation Matrices for Small-Cap-Inclusive Portfolios

arXiv:2608.30446v1 Announce Type: cross Abstract: Small-cap-inclusive equity universes contain recently listed and intermittently traded securities, so enforcing a common look-back discards a substant

researcharxiv-cs-lg

Enhancing SAE-based Steering via Neighbor Integrated Feature Selection

arXiv:2608.28806v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) disentangle model activations into interpretable features and are widely used for steering large language models. Most existi

Local Ai

EpaCache: Error-Propagation-Aware Caching for Accelerating Diffusion-Based Visual Generation

arXiv:2608.29264v1 Announce Type: new Abstract: Diffusion-based visual generative models deliver strong image and video synthesis quality but incur high inference costs because sequential samplers rep

local-aiarxiv-cs-ai

Error-Driven Scene Editing for 3D Grounding in Large Language Models

arXiv:2511.14086v2 Announce Type: replace-cross Abstract: Despite recent progress in 3D-LLMs, they remain limited in accurately grounding language to visual and spatial elements in 3D environments. Th

Tutorials

Everybody Tracking Every Body

arXiv:2608.29927v1 Announce Type: new Abstract: We address the problem of 3D body pose estimation of multiple interacting people from their egocentric views with centralized coordination. Each individ

tutorialsarxiv-cs-cv

Local Ai

Explainable Multi-Loss Distillation Framework for Efficient and Interpretable Shrimp Disease Text Classification

arXiv:2608.29027v1 Announce Type: new Abstract: Shrimp disease classification has become an urgent issue due to its significant impact on the import-export output of producing countries, particularly

local-aiarxiv-cs-cv

FaceSnap: Real-Time Personalized Lightstage Facial Performance Capture

arXiv:2608.31033v1 Announce Type: new Abstract: Lightstage facial capture produces production-quality digital humans, but it is resource and labor-intensive. Multi-camera setups, hours of computation,

Faithfulness Is Not Free: Auditing Offline KV-Cache Quantization in Retrieval-Augmented Generation

arXiv:2608.30996v1 Announce Type: new Abstract: Retrieval-augmented generation systems can precompute and store key-value caches of retrieved documents to avoid re-encoding context at every query. Qua

researcharxiv-cs-cl

Federated Multi-Task Learning for Bladder Tumor Segmentation and MIBC Classification Using a Hybrid CNN-Transformer Architecture

arXiv:2608.30458v1 Announce Type: new Abstract: Accurate bladder tumor segmentation and assessment of mus- cle invasion from T2-weighted MRI are important for treatment plan- ning, but developing robu

Federated Personalization of Early-Exit Networks

arXiv:2601.10015v2 Announce Type: replace Abstract: Personalized Federated Learning (PFL) excels at tailoring client-specific models, which is particularly critical for decentralized and heterogeneous

applicationsarxiv-cs-lg

FigMirror: Ground It, Code It, Plot It

arXiv:2608.28814v1 Announce Type: cross Abstract: Converting scientific figures into executable code has gained increasing attention, yet existing methods primarily focus on reproducing the reference

FISICA: A Deployed Service for Plantar-Pressure and Posture Assessment with Ontology-Grounded Recommendation

arXiv:2608.29336v1 Announce Type: new Abstract: FISICA is a body-assessment and recommendation service running in production. One standing session with two photographs returns foot-loading measures, p

applicationsarxiv-cs-cv

Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps

arXiv:2608.29615v1 Announce Type: cross Abstract: Across industries, machine-learning systems support applications ranging from prediction and anomaly detection to forecasting, optimization, and sched

safetyarxiv-cs-ai

Tutorials

FoundDiff: Foundational Diffusion Model for Generalizable Low-Dose CT Denoising

arXiv:2508.17299v2 Announce Type: replace Abstract: Low-dose computed tomography (CT) denoising is crucial for reduced radiation exposure while ensuring diagnostically acceptable image quality. Despit

tutorialsarxiv-cs-cv

Frequency Selective Neural Networks as a Foundation Architecture for Time Series Learning

arXiv:2608.29012v1 Announce Type: new Abstract: Time-series data across physical and biological domains are fundamentally driven by complex, non-stationary oscillatory modes. While deep learning model

Agents

From Extraction to Governed Memory: Multi-Agent Knowledge Graph Construction with Domain-Expert Review

arXiv:2608.28642v1 Announce Type: new Abstract: Knowledge graphs used by agentic systems are often treated as flat stores of extracted triples, with little record of who owns a fact, why it was admitt

agentsarxiv-cs-ai

Agents

From Final Artifacts to Trajectories: Retrospective Process Supervision for Evidence-Grounded Long-Form Generation

arXiv:2608.30461v1 Announce Type: new Abstract: Trajectory data is getting more vital for training large language models for boosting the agentic abilities. Unlike the verifiable domains such as codin

agentsarxiv-cs-cl

From Location Phrases to Geographic Entities: Task-Adapted Retrieval for People Search

arXiv:2608.28965v1 Announce Type: new Abstract: People search must map free-form location phrases to geographic entities used as structured retrieval filters. Lexical standardizers handle canonical na

From Metaheuristics to Exact Methods: A CP-SAT Approach for Multi-Objective Healthcare Workforce Scheduling

arXiv:2608.30419v1 Announce Type: new Abstract: Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, empl

applicationsarxiv-cs-ai

FuncRoom-Agent: Sequential Feed-Forward 3D Functional Indoor Scene Generation

arXiv:2608.29519v1 Announce Type: new Abstract: We introduce Function-Room Generation, a new indoor 3D scene generation setting that creates rooms supporting explicit functional goals rather than mere

Game-Agnostic Value Functions through Automatic JSON Feature Extraction

arXiv:2608.30056v1 Announce Type: new Abstract: JSON Bag-of-Tokens (JSON-Bag) is a recently proposed method to generically represent game trajectories by tokenizing their JSON descriptions. We introdu

Generalizable Multi-Agent Planning from Signal Temporal Logic Specifications via Diffusion

arXiv:2608.29490v1 Announce Type: cross Abstract: Multi-agent systems in the real-world (e.g., drone swarms, autonomous cars, warehouse robots) must satisfy rich, temporal tasks while avoiding collisi

safetyarxiv-cs-ai

Generation of High-Level Concepts in 3D Scene Graphs via Autoregressive Diffusion

arXiv:2608.28733v1 Announce Type: cross Abstract: Indoor 3D Scene Graphs (3DSGs) represent environments as multi-layer hierarchies that connect observed geometric primitives (e.g., planes) to higher-l

researcharxiv-cs-lg

Geometric Attractor Monitoring: A Robust and Frugal Framework for Multi-modal Industrial Robotic Cycles

arXiv:2608.30804v1 Announce Type: new Abstract: Monitoring the health of heterogeneous industrial robot fleets is severely challenged by the multi-modal nature of their operational cycles and a persis

safetyarxiv-cs-lg

Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs

arXiv:2608.30437v1 Announce Type: new Abstract: Graph-augmented large language models often assume that graph evidence produced by external computation and placed in the input can be used by the nativ

safetyarxiv-cs-cl

GreenBench: Benchmarking Energy Efficiency and Carbon Footprint of Open-Source LLM Inference on Apple Silicon

arXiv:2608.28667v1 Announce Type: cross Abstract: The rapid proliferation of Large Language Models (LLMs) has raised concerns about their environmental impact during inference. While Green AI research

GridFlow: Structured Latent Flow for Seamless City-Scale 3D Point Cloud Generation

arXiv:2608.29793v1 Announce Type: new Abstract: Generating realistic 3D city environments from remote sensing data is important for simulation, urban planning, and mixed reality, yet existing point cl

GUIDE: Guiding Internal Evidence with Language Instructions

arXiv:2608.30712v1 Announce Type: new Abstract: Large multimodal models follow instructions about what to generate, but not necessarily about what evidence to rely on. Hence, models may continue to de

HANIA: Planner-Guided Multimodal Graph Evidence Selection for Grounded Question Answering

arXiv:2608.29088v1 Announce Type: new Abstract: Multimodal question answering remains sensitive to noisy, incomplete, and weakly grounded evidence. Long unstructured contexts can introduce redundancy

Hi-Q: Hierarchical Evidence-guided Query Refinement for Multi-Hop Question Answering

arXiv:2608.30468v1 Announce Type: new Abstract: A central bottleneck in multi-hop Question Answering (QA) is that the granularity at which a question is expressed often differs from the granularity at

researcharxiv-cs-cl