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DF^3: World Modeling via Decoder-Free Feature Forecasting in Autonomous Navigation

arXiv:2608.02428v1 Announce Type: new Abstract: Forecasting future states from video sequences is a critical challenge for autonomous robotic systems and a fundamental objective of world modeling. Pri

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Diagnosing Search Behavior and Failure Modes in Long-Horizon Search Agents

DGX agent

arXiv:2608.01913v1 Announce Type: cross Abstract: Deep search agents answer difficult information-seeking questions by iteratively issuing search queries to gather supporting evidence, but it remains

agentsarxiv-cs-cl

4 Aug 2026

Diagnosing Under-Development of Irreversible Processes in Video Generation

arXiv:2608.00617v1 Announce Type: new Abstract: Many physical attributes are irreversible: ice melts but does not re-freeze, paper chars but does not un-burn. Do video generators respect this? We show

Differentiable Lifting for Topological Neural Networks

arXiv:2608.01160v1 Announce Type: new Abstract: Topological neural networks (TNNs) enable leveraging high-order structures on graphs (e.g., cycles and cliques) to boost the expressive power of message

DiffPhysCam: Differentiable Physics-Based Camera Simulation for Inverse Rendering and Embodied AI

arXiv:2508.08831v2 Announce Type: replace-cross Abstract: Generating synthetic images that closely mimic those from real cameras is instrumental in training visual models and enabling end-to-end visuo

DiffPrune: differentiable information throttling for token pruning in vision-language models

arXiv:2608.01985v1 Announce Type: new Abstract: Visual token pruning reduces the computational cost of Vision-Language Models (VLMs) by removing redundant visual tokens. The key is to learn a score th

tutorialsarxiv-cs-cv

DiffuseAgent-MI: Distributionally-Grounded,Tool-Integrated Self-Evolving Agents for Faithful Visual Reasoning

arXiv:2608.00540v1 Announce Type: new Abstract: Tool-integrated vision-language agents have made remarkable progress on compositional and multi-step visual reasoning. Yet their outputs frequently exhi

safetyarxiv-cs-cv

Diffusion-Based Body Schema Learning Enabling Abnormal-State Adaptation in Musculoskeletal Robots

arXiv:2608.01029v1 Announce Type: new Abstract: Musculoskeletal robots require an internal body schema that remains consistent under a wide range of physical state changes, including abnormalities suc

tutorialsarxiv-cs-ro

Diffusion Policy with Behavioral Advantage Correction for Offline Reinforcement Learning

arXiv:2608.02332v1 Announce Type: new Abstract: In offline reinforcement learning (RL), the distribution shift between behavioral data and the learned policy can lead to erroneous Q-value estimation,

safetyarxiv-cs-lg

DiffusionGemma Technical Report

arXiv:2608.00146v1 Announce Type: new Abstract: We introduce DiffusionGemma, an experimental open-weight language model that uses discrete diffusion to generate text at exceptionally high speed. Rathe

Direct and Adaptable Mesh-Gaussian Scene Reconstruction from Multi-View Images

arXiv:2405.06945v4 Announce Type: replace Abstract: Jointly recovering explicit surface geometry and high-quality appearance from multi-view images remains challenging. This capability is essential fo

Disagree to Accelerate: Closing the Loop on Diffusion Feature Forecasts

arXiv:2608.01740v1 Announce Type: new Abstract: Training-free feature forecasting accelerates diffusion sampling by predicting features at skipped denoising steps. Recent work has mainly focused on de

tutorialsarxiv-cs-lg

Discriminative Axis, Not Data Volume: What a Contrastive Corpus Teaches an Audio Embedding

arXiv:2608.01560v1 Announce Type: new Abstract: Scaling the corpus is the default remedy when a contrastive representation lacks an attribute. We report a case where it does nothing, and identify what

researcharxiv-cs-cl

Disentangled Contrastive Learning for Zero-Shot Multilingual Dense Retrieval

arXiv:2608.02189v1 Announce Type: cross Abstract: Multilingual dense retrieval aims to handle queries and documents across different languages based on a unified retriever model. The challenge lies in

safetyarxiv-cs-cl

Disentangling Visuo-Tactile Foresight: Oracle-Guided Interface Discovery for World Action Models

model-releasesarxiv-cs-ro

arXiv:2608.00547v1 Announce Type: new Abstract: Contact-rich manipulation remains challenging because successful control depends on physical interaction cues that are often weakly observable from visi

Distill What RGB Can Recover: Privileged 3D Evidence for RGB-Only Vision-Language Models

arXiv:2608.00110v1 Announce Type: new Abstract: 3D scene understanding requires reasoning about entity existence, spatial layout, and object relations, yet RGB images alone often provide insufficient

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

Distill Where You Fail: Recovering Learning Signals of Negative RL-Groups from Adaptive Teacher Guidance

arXiv:2608.00782v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training large language models (LLMs). While Group Relativ

safetyarxiv-cs-cl

Distilling Drifting Transformers with Representation Autoencoders

arXiv:2606.15553v2 Announce Type: replace Abstract: Despite the significant training acceleration and promising performance, Representation Autoencoders (RAEs) are mainly criticized for poor distillat

Distributional Matching for Vector Quantization: A Unified Theoretical and Empirical Framework

arXiv:2607.15933v2 Announce Type: replace Abstract: The effectiveness of modern visual representation learning and autoregressive models critically depends on vector quantization (VQ), which discretiz

Divergent large language model predictions from convergent representations in ambiguous word pairs

arXiv:2608.01816v1 Announce Type: new Abstract: In this work we investigate how decoder-only transformers resolve lexical ambiguity through layer-by-layer analysis of three models spanning three param

DLLM-TTS: Block Discrete Diffusion Language Model for Text-to-Speech Synthesis

arXiv:2608.00011v1 Announce Type: new Abstract: Current text-to-speech systems face a trade-off: autoregres- sive codec language models produce highly intelligible speech but require large-scale model

Do Maps Still Matter for Machines: Revisiting the Role of Choropleth Maps in Foundation Model Spatial Understanding

arXiv:2607.17999v2 Announce Type: replace-cross Abstract: Spatial understanding is crucial for foundation models (FMs), and maps have long helped humans organize and reason about geographic informatio

Do Neural Networks Really Beat the Curse of Dimensionality? A Bit-Complexity View

arXiv:2608.01357v1 Announce Type: new Abstract: Traditional approximation theory measures convergence rates in terms of the number of parameters or degrees of freedom. However, practical computation o

Do Static Embeddings Add Value to Hybrid Dutch Retrieval?

model-releasesarxiv-cs-lg

arXiv:2608.02112v1 Announce Type: new Abstract: Embedding benchmarks measure standalone model quality, but they do not establish whether a low-cost retriever contributes complementary ranking informat

DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering

arXiv:2608.01565v1 Announce Type: new Abstract: Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers st

agentsarxiv-cs-cl

DocPO: Advancing Document Policy Optimization via Tailored Step-Aware Rewards

arXiv:2608.00536v1 Announce Type: new Abstract: Reinforcement learning (RL) for document parsing often relies on reference-based rewards rooted in edit distance (e.g., tree edit distance), yet it rema

safetyarxiv-cs-cv

DODA: A Database of Datasets for Aesthetics Research

arXiv:2608.00089v1 Announce Type: new Abstract: With rapid growth in the fields of empirical and computational aesthetics we have seen a vast increase in large image datasets annotated for aesthetics.

Does Accuracy Equal Evidence? Reasoning Faithfulness under KV Cache Compression

arXiv:2608.01631v1 Announce Type: new Abstract: KV cache compression is commonly evaluated by final-answer accuracy, implicitly assuming that preserving the answer also preserves the reasoning that su

researcharxiv-cs-cl

Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs

arXiv:2608.02396v1 Announce Type: new Abstract: Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural network

Does Machine 'know' interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse

arXiv:2608.01174v1 Announce Type: new Abstract: This study examines Transformer-based models' ability to learn emoji pragmatics in Arabic digital discourse (ADD), providing evidence from MARBERT's beh

tutorialsarxiv-cs-cl

Does the Competitive Component of Adversarial Self-Play Improve Legal Reasoning? A Controlled Negative Result

arXiv:2608.01559v1 Announce Type: cross Abstract: Adversarial self-play is an appealing recipe for legal reasoning: have a student model draft an argument, have an adversary attack it, and reward the

applicationsarxiv-cs-cl

Domain-Generalized Adaptive Semantic Communication for Collaborative Perception

arXiv:2608.00056v1 Announce Type: cross Abstract: We propose RSTA, a domain-generalized semantic communication framework enabling source-free V2X collaborative perception under both observation-domain

safetyarxiv-cs-lg

Domain-Specific Evaluation of Text-to-Speech Systems: A Multi-Metric Benchmarking Study

arXiv:2608.02235v1 Announce Type: new Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages. However

Dominant Arm Identification with Mixing and Recycling Observed Samples

arXiv:2608.01545v1 Announce Type: cross Abstract: We study the problem of identifying the dominant arm in multi-armed bandits, where the objective is to find the action with the highest probability of

Don't Judge a Book by its Cover: Testing LLMs' Robustness Under Logical Obfuscation

arXiv:2602.01132v2 Announce Type: replace Abstract: Tasks such as solving arithmetic equations, evaluating truth tables, and completing syllogisms are handled well by large language models (LLMs) in t

Don't Offer What Can't Be Done: Deterministic Executability Gating for LLM Skill Selection at Scale

arXiv:2608.01050v1 Announce Type: cross Abstract: Production LLM agents that select from large skill libraries face a limitation that semantic relevance alone cannot resolve: a skill may match a user'

applicationsarxiv-cs-cl

Douyin Multimodal Embedding Model Technical Report

arXiv:2608.02148v1 Announce Type: cross Abstract: Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search

applicationsarxiv-cs-cl

DPL: Depth-only Perceptive Humanoid Locomotion via Realistic Depth Synthesis and Cross-Attention Terrain Reconstruction

arXiv:2510.07152v3 Announce Type: replace Abstract: Recent advancements in legged robot perceptive locomotion have shown promising progress. However, terrain-aware humanoid locomotion remains largely

safetyarxiv-cs-ro

DrawAI: Agentic Benchmark and Workflow for Making Raster Images Editable

arXiv:2608.00548v1 Announce Type: new Abstract: Recent image-generation models and multimodal agents can produce high-quality visuals for increasingly complex visual communication tasks. Yet their ras

DreamTraj: Generating 6-DoF Object Trajectories by Reading Unrendered Video Diffusion Latents

arXiv:2608.00486v1 Announce Type: new Abstract: Accurate prediction of object trajectories during manipulation is essential for closing the perception-action loop. Progress is limited on two fronts: a

DreamTrajectory: Trajectory-Guided Action Generation with World Model Alignment for Mobile Manipulation

arXiv:2608.01381v1 Announce Type: new Abstract: Mobile manipulation requires a robot to coordinate base and arm motion under continuously changing viewpoints and contact conditions, within an action s

safetyarxiv-cs-ro

DriveCode: Domain Specific Numerical Encoding for LLM-Based Autonomous Driving

arXiv:2603.00919v3 Announce Type: replace Abstract: Large language models (LLMs) have shown great promise for autonomous driving. However, discretizing numbers into tokens limits precise numerical rea

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

DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments

arXiv:2608.00402v1 Announce Type: new Abstract: Estimated Time of Arrival (ETA) prediction is a core component of intelligent transportation systems. As traffic congestion patterns become increasingly

applicationsarxiv-cs-lg

DS@GT ARC at MEDIQA-CORE-Task-1 2026: Trimodal Model Fusion with Task-Specific Gates for Brain Tumor Subtype Classification

arXiv:2608.00086v1 Announce Type: new Abstract: Brain tumor diagnosis is a time-sensitive process in which patients may wait weeks for a finalized pathology report. This problem motivates automated sy

Local Ai

DyFrDet: Towards Accurate Small Object Detection via Dynamic Frequency Suppression with Label Disambiguation

arXiv:2608.02495v1 Announce Type: new Abstract: Despite the remarkable progress over the past decades, accurately identifying small objects remains challenging because of their insufficient visual cue

local-aiarxiv-cs-cv

DynActiveGS: Active Gaussian Splatting for Dynamic Scene Reconstruction

arXiv:2608.01178v1 Announce Type: new Abstract: We present DynActiveGS, a dynamic-aware active reconstruction framework based on 3D Gaussian Splatting (3DGS) for autonomous exploration in dynamic envi