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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

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Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models

DGX agent

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

4 Aug 2026

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

Agents

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

Tutorials

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

Agents

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

agentsarxiv-cs-cv

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

Agents

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

agentsarxiv-cs-cv

Local Ai

Dynamic Resolution Routing for Efficient Egocentric Grounding

arXiv:2608.01638v1 Announce Type: new Abstract: Egocentric visual grounding requires high-resolution inputs to localize small objects. However, scaling Multimodal Large Language Models to this domain

local-aiarxiv-cs-cv

Dynamic UAV-based search operations using probabilistic diffusion modeling of Man Overboard incident victims

arXiv:2608.02093v1 Announce Type: new Abstract: More than 70% of the people that fell overboard cruise ships in the period 2010-2019 lost their lives. This paper presents a strategy for reliably predi

researcharxiv-cs-ro

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration

arXiv:2608.01452v1 Announce Type: cross Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that a

DynamicWAM: Dual-Path Motion Conditioning for World-Action Models in Dynamic Manipulation

arXiv:2608.00793v1 Announce Type: new Abstract: Dynamic manipulation requires robots to infer target motion and respond promptly, yet existing World-Action Models (WAMs) typically condition only on th

applicationsarxiv-cs-ro

DynImmune-BERT: Dynamic Immune Repertoire Modeling with Neural ODE Driven Continuous Transformers

model-releasesarxiv-cs-lg

arXiv:2607.17244v2 Announce Type: replace Abstract: Longitudinal T cell receptor repertoires contain signals of clonal expansion, contraction, disappearance, and reappearance after immune perturbation

E2Pano: Learning Event-to-Panorama Image Reconstruction

arXiv:2608.00694v1 Announce Type: new Abstract: Event cameras offer microsecond-level temporal resolution and high dynamic range, potentially facilitating motion-blur-free panoramic imaging from fast

Hardware

early sparks of rsi? Ali Taha @waterloo_intern explains how http://Z.ai's GLM-5.2 (@Zai_org) profiled its SGLang serving path and rewrote bo…

early sparks of rsi? Ali Taha @waterloo_intern explains how http://Z.ai's GLM-5.2 (@Zai_org) profiled its SGLang serving path and rewrote bottlenecked GPU kernels, (still lacks reliable judgment) grea

hardwareswyx--x

EchoCache: Energy-Guided Cross-Modal Caching for Efficient Audio-Driven Video Generation

arXiv:2608.02474v1 Announce Type: new Abstract: Audio-driven video generation (A2V) has achieved promising progress in synthesizing temporally coherent and audio-visually aligned videos, yet its infer

EEG-FM-Compass: Progress, Benchmarking, and Future Directions for EEG Foundation Models

arXiv:2601.17883v3 Announce Type: replace-cross Abstract: Electroencephalography (EEG) foundation models (FMs) have recently emerged as a promising paradigm for brain-computer interfaces, aiming to le

Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs

model-releasesarxiv-cs-lg

arXiv:2511.00382v2 Announce Type: replace-cross Abstract: Organizations increasingly adapt Large Language Models (LLMs) from public repositories such as HuggingFace to downstream tasks. Prior work sho

Local Ai

Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

arXiv:2409.05885v2 Announce Type: replace Abstract: Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehens

local-aiarxiv-cs-lg

Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data

arXiv:2608.02580v1 Announce Type: new Abstract: Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich

researcharxiv-cs-ro

EgoIntent: A Pre-Outcome Micro-Step Benchmark for Understanding What, Why, and Next

arXiv:2603.12147v2 Announce Type: replace Abstract: Egocentric video provides a natural modality for studying human behavior, but conventional visual understanding captures mainly observable scenes, o

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

arXiv:2506.04831v3 Announce Type: replace-cross Abstract: Forecasting how a patient's condition is likely to evolve, including possible deterioration, recovery, treatment needs, and care transitions,

researcharxiv-cs-cl

Eigenvalues as a Metric for Memory Dynamics in Sequence Models

arXiv:2510.09379v2 Announce Type: replace Abstract: While softmax attention drives state-of-the-art performance in sequence modeling, its quadratic complexity motivates linear alternatives such as sta