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Diversity is Not Ambiguity: Toward Accurate and Efficient Ambiguity Detection for Open-Domain QA

arXiv:2608.03177v1 Announce Type: new Abstract: How can question answering (QA) systems determine whether a query is ambiguous? Ambiguity detection is essential in open-domain QA, as misclassification

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Tutorials

Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model

DGX agent

arXiv:2608.03566v1 Announce Type: cross Abstract: The drift diffusion model (DDM) is a cornerstone of cognitive decision-making research. Although numerous estimation methods exist, researchers contin

tutorialsarxiv-cs-lg

5 Aug 2026

DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

arXiv:2608.03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneo

Document OCR is not Getting Commoditized (by Frontier Models) The most common question I get is whether frontier models are going to eat all…

model-releasesjerry-liu--x

Document OCR is not Getting Commoditized (by Frontier Models) The most common question I get is whether frontier models are going to eat all document processing solutions - just screenshot the page an

Does Forgetting Transfer Across Modalities? A Real-World Benchmark for Cross-Modal Knowledge Unlearning Evaluation

arXiv:2608.03791v1 Announce Type: new Abstract: Vision-Language Models (VLMs), like Large Language Models (LLMs), may memorize sensitive, copyrighted, or harmful knowledge from their pretraining corpo

Don't Let Me Ask for It: LLMs Show Deficiencies in Active Multi-Turn Information Acquisition for Abductive Inference

arXiv:2608.03388v1 Announce Type: new Abstract: Abductive reasoning requires forming hypotheses that explain observed evidence and revising them as new evidence becomes available. While large language

researcharxiv-cs-cl

Don't Peek at the Answer: Outcome-Masked Group Relative Policy Optimization for Label-Free RLVR

arXiv:2608.03119v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves LLM reasoning but typically relies on ground-truth (GT) answers, limiting scalability. Vo

Agents

Don't Regenerate, Debug: A Domain-Specific Agent for Repairing Near-Miss Hardware Operators

arXiv:2608.02712v1 Announce Type: cross Abstract: Kernel generation for hardware accelerators such as GPUs and NPUs has become a proving ground for large language models (LLMs), and state-of-the-art s

agentsarxiv-cs-ai

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

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

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

researcharxiv-cs-cv

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,

researcharxiv-cs-cv

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

researcharxiv-cs-cv

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

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

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

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