All entries

Don't Walk the Line: Boundary Guidance for Filtered Generation

arXiv:2510.11834v3 Announce Type: replace-cross Abstract: Generative models are increasingly paired with safety classifiers that filter harmful or undesirable outputs. A common strategy is to fine-tun

dots.tts.edit: Precisely Controlled Speech Editing with a Continuous Autoregressive Model

DGX agent

arXiv:2608.02673v1 Announce Type: cross Abstract: Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language pr

model-releasesarxiv-cs-ai

5 Aug 2026

Double Descent in Gradient Boosting Decision Trees via Split-Candidate Scaling

model-releasesarxiv-cs-lg

arXiv:2608.03111v1 Announce Type: new Abstract: Double descent is commonly studied by scaling an explicit capacity parameter, such as neural-network width. For gradient boosting decision trees (GBDTs)

Double Down on Defense: Strengthening Deep Perceptual Hashes against Evasion Attacks without Retraining

arXiv:2608.03101v1 Announce Type: new Abstract: Near-duplicate image matching is crucial for trust and safety, provenance verification, copyright enforcement, and large-scale visual search. Modern pla

DP-MemView: A Memory Interface for Attribute-Level Transcript Privacy in Long-Term LLM Agents

arXiv:2608.03130v1 Announce Type: cross Abstract: Long-term memory enables persistent personalization in LLM agents, but repeated memory-conditioned responses can cumulatively reveal protected attribu

Agents

Dr. AGENTONOMICS: A Didactic Experiment of AGENTONOMICS

arXiv:2608.03524v1 Announce Type: new Abstract: AGENTONOMICS is a framework that treats AI agents as economic entities that can be designed, managed, and governed through an integrated management arch

agentsarxiv-cs-ai

DRIFT: Derailing Denoising Trajectories of Flow-Matching VLAs with Adversarial Patch Attack

arXiv:2608.03207v1 Announce Type: new Abstract: Flow-matching vision-language-action (VLA) models such as pi0 generate robot actions by integrating a learned denoising velocity field, and have been re

DriftWorld: Fast World Modeling through Drifting

arXiv:2607.15065v2 Announce Type: replace-cross Abstract: Predictive world models enable robots to plan by imagining the outcomes of their actions, but their value for control hinges on generating man

DRPFNet: Dual-domain Residual Progressive Fusion Network for RGB-Thermal Object Detection

arXiv:2608.03370v1 Announce Type: new Abstract: RGB-thermal (RGB-T) object detection aims to fuse complementary information from visible and thermal modalities to achieve robust detection under varyin

DS@GT-ARC at eRisk 2026 Task 3: Sparse, Semantic, and LLM Reranking for ADHD Symptom Sentences

arXiv:2608.03883v1 Announce Type: new Abstract: This paper describes our submissions to eRisk 2026 Task 3, ADHD Symptom Sentence Ranking. The task requires systems to rank candidate Reddit sentences a

Dual-domain U-Nets with embedded back projection operators for motion-resolved 4D CBCT reconstruction

arXiv:2608.03430v1 Announce Type: new Abstract: Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times,

DUD: Decoupled Update Dynamics for Reliable Uncertainty Quantification in Large Language Models

arXiv:2608.03411v1 Announce Type: new Abstract: Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics

researcharxiv-cs-cl

Dynamically Allocating Evaluation Effort for Model Ranking

arXiv:2608.03437v1 Announce Type: new Abstract: While human evaluation is the gold standard in many NLP tasks, it suffers from prohibitive costs and poor scalability. When identifying top-performing m

Earth Embeddings

arXiv:2608.03410v1 Announce Type: new Abstract: Earth observation is moving from foundation models that users must run themselves toward embedding products that package model feature outputs as reusab

Tutorials

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density

arXiv:2608.03260v1 Announce Type: new Abstract: Pretraining has shown strong potential for learning transferable representations, yet it remains underexplored for electron-density-based molecular lear

tutorialsarxiv-cs-lg

EditFlow3D: Automated Local Editing of 3D Assets with Trajectory Preservation

model-releasesarxiv-cs-cv

arXiv:2608.03179v1 Announce Type: new Abstract: Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple ye

EduClaw-Bench: A Long-Horizon Benchmark for Pedagogical LLM Agents with Simulated Learners

arXiv:2608.03206v1 Announce Type: cross Abstract: Large language models (LLMs) power educational applications from tutoring to essay scoring, but each is a point solution to a single task, and only re

Efficient Knowledge Distillation for LLMs: Offline Top-K Logits and a Fused Chunked KL Loss

arXiv:2608.03796v1 Announce Type: cross Abstract: Small language models are often the only option for deployment under tight latency, cost, and on-premises constraints, but they are rarely trained fro

Efficient Multilingual Neural Machine Translation via Corpus-Driven Vocabulary Pruning: An English-Arabic Case Study

arXiv:2608.03480v1 Announce Type: new Abstract: The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

Efficient quantum-enhanced classical simulation for patches of quantum landscapes

arXiv:2411.19896v2 Announce Type: replace-cross Abstract: Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does t

researcharxiv-cs-lg

Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

arXiv:2407.21311v2 Announce Type: replace-cross Abstract: Unsupervised domain adaptation (UDA) aims to mitigate domain shift, where the distribution of labeled source data differs from that of unlabel

Efficient Video Dataset Distillation via Cluster-Guided Prototype Blending

arXiv:2608.03269v1 Announce Type: cross Abstract: Video dataset distillation aims to compress a large video dataset into a compact surrogate set that preserves its training utility. Most existing appr

EFX Allocation In (Multi)Hypergraphs

arXiv:2608.03171v1 Announce Type: cross Abstract: We study fair allocations of indivisible goods among agents with heterogeneous monotone valuations. As fair we consider the allocations that are envy-

EmbodiedVAE: Disentangled Video VAE for Efficient and Controllable Embodied Manipulation

arXiv:2608.02990v1 Announce Type: new Abstract: Latent diffusion models (LDMs) have recently significantly advanced embodied learning in constructing powerful embodied manipulation world models. Howev

researcharxiv-cs-ro

Emulate or Estimate? The Divergent Strengths of Base and Post-Trained Language Models for Opinion Simulation

arXiv:2608.03044v1 Announce Type: cross Abstract: Large language models are increasingly used to simulate human opinions, but prior work reports conflicting results: some studies find promising alignm

safetyarxiv-cs-ai

Applications

Enactive Artificial Intelligence: A Decision-Centric Architecture for Complex Systems

arXiv:2608.03413v1 Announce Type: new Abstract: As artificial intelligence (AI) continues to evolve and mature, recent AI practices have moved beyond large language models (LLMs) and text or image gen

applicationsarxiv-cs-ai

Enhanced Polarization Locking in VCSELs

arXiv:2604.01857v2 Announce Type: replace-cross Abstract: While optical injection locking (OIL) of vertical-cavity surface-emitting lasers (VCSELs) has been widely studied in the past, the polarizatio

Enhancing Q-Value Updates in Deep Q-Learning via Successor-State Prediction

arXiv:2511.03836v2 Announce Type: replace Abstract: Deep Q-Networks (DQNs) estimate future returns by learning from transitions sampled from a replay buffer. However, the target updates in DQN often r

safetyarxiv-cs-lg

Enhancing Tabular Learners with Context-Aware Semantic Embeddings

arXiv:2608.03565v1 Announce Type: new Abstract: While modern tabular learners excel at capturing statistical patterns, they frequently operate in a semantic vacuum, treating textual features as discre

Enhancing VLM Reward Models Through Structure-Aware Fine-Tuning

arXiv:2608.03875v1 Announce Type: cross Abstract: Designing effective reward functions remains a major bottleneck in Reinforcement Learning (RL). Recent work uses large foundation Vision-Language Mode

safetyarxiv-cs-ai

Equivariant Music Transformer

arXiv:2608.03920v1 Announce Type: cross Abstract: Humans recognize a musical passage even when it is shifted in time or transposed in pitch, indicating a notion of equivariance in the representation s

Agents

ETA: A New Agentic Paradigm for Embodied Tasks

arXiv:2608.03924v1 Announce Type: new Abstract: When will robots have their ChatGPT moment? Such a breakthrough requires a general-purpose robot that can handle unfamiliar tasks in unfamiliar environm

agentsarxiv-cs-ro

Evading Chain-of-Thought Monitoring Through Model Poisoning

arXiv:2608.02820v1 Announce Type: cross Abstract: Chain-of-thought (CoT) monitoring is an increasingly important component of AI safety stacks but relies on the assumption that a model's reasoning tra

safetyarxiv-cs-ai

Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning

arXiv:2608.03028v1 Announce Type: new Abstract: Applying a valid medication-safety rule when its patient-specific conditions are not met can produce an incorrect decision. Existing medical evaluations

Evaluating LLM Trade-offs for Enterprise Automation: Lessons from Workflow Generation in a Production Enterprise Platform

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

Evaluating LLMs in Database Scenarios: A Lifecycle Benchmark for Assessing Their Potential in Core Database Tasks

arXiv:2608.03794v1 Announce Type: cross Abstract: Large Language Models (LLMs) are transforming database interaction paradigms, evolving from simple query translators to autonomous database administra

Evaluating OpenAI's Privacy Filter: Cross-Lingual, Cross-Domain PII Detection Across 42 Benchmarks

arXiv:2608.02616v1 Announce Type: cross Abstract: We present the first independent, systematic evaluation of OpenAI's Privacy Filter (OPF), a 1.5B-parameter bidirectional PII detector, across 42 synth

Evaluation Blindness: How Silent Measurement Failures Corrupt AI Systems from Training to Deployment

model-releasesarxiv-cs-lg

arXiv:2608.02786v1 Announce Type: new Abstract: AI systems can fail silently. The failure propagates through training loops, evaluation pipelines, and production monitoring stacks until downstream har

Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple-Choice Benchmarks

arXiv:2608.02966v1 Announce Type: new Abstract: Most multiple-choice question (MCQ) benchmarks evaluate Large Language Models (LLMs) only by whether they select the correct answers. This binary scorin

researcharxiv-cs-cl

Evidence-Grounded Multimodal Knowledge Graph Construction for Multi-Lecture Educational Reasoning

arXiv:2608.03161v1 Announce Type: new Abstract: Lecture videos distribute knowledge across speech, slide text, diagrams, equations, and presentation order, which transcript-only retrieval does not ful

EvoHIL: Self-Evolving Reward and Flow-Matched Policy Optimization for Robust Human-in-the-Loop Reinforcement Learning

arXiv:2608.03872v1 Announce Type: new Abstract: Human-in-the-loop reinforcement learning (HIL-RL) enables robots to learn contact-rich manipulation from limited real-world interaction, but deployment

safetyarxiv-cs-ro

Applications

Explainable AI for the EU Right to Explanation: A Systematic Review of the Law-XAI Translation Gap

arXiv:2608.02699v1 Announce Type: new Abstract: When algorithms make or influence consequential decisions---about loan eligibility, hiring, or healthcare---EU law grants affected individuals a Right t

applicationsarxiv-cs-ai

Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2608.03045v1 Announce Type: new Abstract: We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black

Externally Validated Breast Ultrasound Segmentation via Multi-task Learning with BI-RADS-Consistent Morphological Priors

arXiv:2511.15968v2 Announce Type: replace-cross Abstract: External validation of breast ultrasound segmentation models remains limited because internal train--test splits do not capture domain shifts

FACTWASH: Catching AI Rewrites That Wash Hearsay into Fact

arXiv:2608.03372v1 Announce Type: cross Abstract: AI systems rewrite information constantly: conversations become stored memories, documents become answers. The rewrite can keep a claim while washing

Fail-Fast, Restart-Smart: Early Failure Prediction and Restart for SWE Agentic Tasks

arXiv:2608.03222v1 Announce Type: cross Abstract: Software engineering (SWE) agents resolve repository-level issues through long trajectories that grow increasingly expensive as context accumulates. F

Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement

arXiv:2608.03733v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-

FaithIR: Rethinking Infrared Image Super-Resolution from Perceptual Sharpness to Task Relevant Fidelity

arXiv:2608.03106v1 Announce Type: new Abstract: Infrared image super-resolution (IISR) is important for downstream tasks such as object detection and semantic segmentation. Existing IISR methods often