All entries

arXiv:2608.08794v1 Announce Type: new Abstract: Omni-modal LLMs jointly process audio, video, and text, but long multimodal sequences incur substantial prefill and KV-cache costs. Existing omni-modal

local-aiarxiv-cs-ai

Agents

Defining Decentralization: An Ontological Perspective

DGX agent

arXiv:2608.09748v1 Announce Type: cross Abstract: Decentralization as a concept in computer science has existed for over half a century. Despite its fundamental role across domains such as security, d

agentsarxiv-cs-ai

11 Aug 2026

Tutorials

Degradation-Guided Underwater Image Restoration with Task-Oriented Latent Control

arXiv:2608.08661v1 Announce Type: new Abstract: Degradation information in underwater images plays a dual role: its spatial and spectral cues can guide adaptive restoration, while degradation-entangle

tutorialsarxiv-cs-cv

Degraded Infrared Small Object Detection via Degradation-Adapted Physics-Guided Restoration

arXiv:2608.09311v1 Announce Type: new Abstract: Infrared small object detection has made significant progress in recent years. However, degradations such as fog and nonuniformity can suppress target-b

Demystifying Prediction Powered Inference

arXiv:2601.20819v2 Announce Type: replace-cross Abstract: Machine learning predictions are increasingly used to supplement incomplete or costly-to-measure outcomes in fields such as biomedical researc

safetyarxiv-cs-lg

Dense Point-to-Mask Optimization with Reinforced Point Selection for Crowd Instance Segmentation

arXiv:2604.01742v2 Announce Type: replace Abstract: Crowd instance segmentation is a crucial task with a wide range of applications, including surveillance and transportation. Currently, point labels

safetyarxiv-cs-cv

Deployable Per-Instance Multi-Layer Activation Steering for Large Language Models

arXiv:2608.08829v1 Announce Type: cross Abstract: Activation steering edits the behaviour of a frozen language model by adding a learned vector to its residual stream, and current practice fixes the i

Deploying Anthropic Claude apps gateway for AWS for enterprise workloads

model-releasesaws-ml-blog

Claude apps gateway is a self-hosted governance layer between Claude Code and Claude Desktop and Amazon Bedrock or Claude Platform on AWS. This post presents a production reference deployment covering

Hardware

Depth-adaptive Inference of Looped Language Models via Continuous Depth Batching

arXiv:2608.09444v1 Announce Type: cross Abstract: A main promise of looped language models (LMs) is depth-adaptive inference. By iterating a block of shared layers a variable number of times, the mode

hardwarearxiv-cs-cl

Depth-Aware Implicit Neural Representation Priors for 3D Gravity Inversion

arXiv:2608.08959v1 Announce Type: new Abstract: Gravimetry images subsurface density contrasts associated with geological structures, geothermal systems, and intrusive bodies. Recovering a three-dimen

Describe-to-Score: A text-guided framework for image complexity assessment

arXiv:2509.16609v2 Announce Type: replace Abstract: Accurately assessing image complexity (IC) is essential for many vision tasks, yet existing approaches rely almost exclusively on visual features an

Hardware

Design Space of Self--Consistent Electrostatic Machine Learning Interatomic Potentials

arXiv:2603.14700v2 Announce Type: replace-cross Abstract: Machine learning interatomic potentials (MLIPs) have become widely used tools in atomistic simulations. For much of the history of this field,

hardwarearxiv-cs-lg

Designing for Ethical AI: HCI Feature Considerations to Improve Fairness and User Experience in AutoML use for Human Resources

arXiv:2608.07477v1 Announce Type: cross Abstract: This thesis examines the fairness of Automated Machine Learning (AutoML) tools in human resource hiring systems through the combined lenses of regulat

Detecting Clear Contact Lenses for Iris Recognition: A Two-Stage Mask-Guided Attention Approach

arXiv:2608.08977v1 Announce Type: cross Abstract: This work focuses on the impact and detection of clear contact lenses in the context of iris recognition. While the detection of cosmetic or patterned

Detection of Self-Introductions in Legislative Testimony

arXiv:2608.07891v1 Announce Type: new Abstract: Self-introductions are common in legislative committee testimonies. Successfully detecting them and extracting the speaker's name is enormously helpful

researcharxiv-cs-cl

Determinization in Structure Theories: A Unified Framework via Closure, Comparability, and Joint Admissibility

arXiv:2608.07476v1 Announce Type: new Abstract: We develop a formal framework for constructing canonical interpretations from plural structure theories. A structure theory is a triple T = ({Sigma}, A,

DevIntent: How Much Does LLM-Generated Code Violate Developer Intent?

model-releasesarxiv-cs-cl

arXiv:2608.07614v1 Announce Type: cross Abstract: Code generated by LLMs can violate a developer's implicit intentions when given an ambiguous prompt, yet standard benchmarks measure only whether code

DH-VLM: Dual-Horizon Cooperative Latent Reasoning for Autonomous Driving

arXiv:2608.09333v1 Announce Type: new Abstract: Large-scale language models for autonomous driving enable enhanced global understanding and long-horizon planning. However, when deployed in isolated ve

safetyarxiv-cs-ro

Diagnosing as Cardiologists Do: ECG Agents with Doctor-Grounded Priors for Clinical Reasoning Across Diseases and Populations

arXiv:2608.09053v1 Announce Type: cross Abstract: Cardiologists interpret electrocardiograms by localizing waveform components, measuring rhythm and interval patterns, and translating these structured

DialectS2S: End-to-End Speech Dialogue Modeling for Low-Resource Chinese Dialects

arXiv:2608.08067v1 Announce Type: cross Abstract: Current end-to-end speech dialogue models are primarily optimized for mainstream languages and remain limited in low-resource dialect scenarios due to

Tutorials

Did the Grid Erase the Event? EndoClock for Auditing Medical World-Model Pipelines

arXiv:2608.09266v1 Announce Type: new Abstract: Medical world models commonly learn from multimodal recordings synchronized onto a fixed-rate grid. This preprocessing resamples each native stream onto

tutorialsarxiv-cs-cv

Different Feedback, Different Updates: Selective Self-Learning from User Interactions for Large Language Models

arXiv:2608.09109v1 Announce Type: new Abstract: User feedback offers natural supervision for persistent LLM improvement, but a single message may support multiple behavioral changes with different sco

Hardware

Differentiate the Solver, Not the Equation: Reverse-Sweep Adjoints for Block Implicit Simulation

arXiv:2608.08559v1 Announce Type: cross Abstract: Differentiable simulation is a key component in learning, control, and inverse problems, where gradients through nonlinear implicit solvers are requir

hardwarearxiv-cs-lg

DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging

arXiv:2608.09445v1 Announce Type: cross Abstract: Unconditional diffusion checkpoint merging assumes benign sources, yet a compromised public checkpoint can transfer a dormant backdoor while clean gen

Diffuse the object, keep its label: curating detector training data from a few unlabeled photographs via VLM-built 3D vegetation scenes

arXiv:2608.09691v1 Announce Type: new Abstract: Labeled images of small objects hidden in vegetation are scarce, and detectors trained on them generalize poorly across sites. Rather than reusing label

Local Ai

Diffusion Image Editing via Asynchronous Token Decoding

arXiv:2608.09322v1 Announce Type: new Abstract: Text-guided diffusion image editing aims to modify semantic attributes of an image while preserving its identity, layout, and background. However, naive

local-aiarxiv-cs-cv

Diminishing Returns of Intelligence: The Non-Linear Relationship Between LLM Scale and User Perception in Short-Duration Open-Ended Social Human-Robot Interactions

model-releasesarxiv-cs-ro

arXiv:2608.08320v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to drive embodied social agents, yet it remains unclear whether larger models improve user perception

DINO-3DRA: Leveraging 2D Foundation Model Semantics for 3D Cerebral Aneurysm Segmentation

arXiv:2608.07767v1 Announce Type: new Abstract: Accurate aneurysm segmentation in 3D rotational angiography (3DRA) is hindered by extreme class imbalance, morphological similarity to vessels, and abse

Directed Neuro-Symbolic Stochastic Execution for Verification of Distributed Parallel AI Programs

arXiv:2608.07947v1 Announce Type: new Abstract: Distributed parallel Artificial Intelligence (AI) programs expose reliability gaps that conventional testing cannot close: parallel executions are non-d

Directional-Clamp PPO

model-releasesarxiv-cs-lg

arXiv:2511.02577v2 Announce Type: replace Abstract: Proximal Policy Optimization (PPO) is widely regarded as one of the most successful deep reinforcement learning algorithms, known for its robustness

DiSCo: Diffusion Sequence Copilots for Shared Autonomy

arXiv:2603.22787v2 Announce Type: replace-cross Abstract: Shared autonomy combines human user and AI copilot actions to control complex systems such as robotic arms. When a task is challenging, requir

safetyarxiv-cs-ro

Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models

arXiv:2601.03115v2 Announce Type: replace Abstract: Emotion is a central dimension of spoken communication, yet, we still lack a mechanistic account of how modern large audio-language models (LALMs) e

safetyarxiv-cs-cl

Discovering Diverse Planning Policies for Multimodal Embodied Agents with Quality-Diversity Optimization

arXiv:2608.08523v1 Announce Type: new Abstract: Multimodal embodied agents are increasingly required to solve long-horizon tasks by integrating visual observations, textual goals, and interaction hist

Disentangling Co-Occurring Retinal Pathologies with Saliency-Guided Sparse Expert Routing

arXiv:2608.09752v1 Announce Type: new Abstract: Retinal fundus images frequently exhibit multiple co-occurring pathologies, yet standard deep learning classifiers apply static, identical computation t

Distill Skills into Weights, Not Prompts: Abstract Skills as Privileged Signals for On-Policy Self-Distillation

arXiv:2608.09826v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards yields no group-relative signal when rollout groups are uniformly correct or uniformly wrong, which acc

DistillCache: KL-Guided Adaptive KV-Cache Eviction for Memory-Efficient LLM Inference

arXiv:2608.08878v1 Announce Type: cross Abstract: Transformer-based large language models (LLMs) achieve strong performance across many tasks, but their Key-Value (KV) cache grows linearly with sequen

Distilling CT Foundation Models into Editable Concept Bottlenecks for Lung Nodule Malignancy Prediction

arXiv:2608.07857v1 Announce Type: cross Abstract: Foundation models provide transferable CT representations, but predictions based directly on these embeddings are difficult to interpret. We developed

Applications

Distilling Physical Priors into Streaming World Models

arXiv:2608.07981v1 Announce Type: new Abstract: Streaming world models predict future visual states online while maintaining physically coherent dynamics over long horizons. However, their rollouts of

applicationsarxiv-cs-cv

Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles

arXiv:2608.08815v1 Announce Type: new Abstract: Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable

safetyarxiv-cs-lg

Local Ai

DistMoE: Private-data Rehearsal-free Routing in Mixture-of-Experts for Distributed Instruction Tuning

arXiv:2608.09907v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong multimodal instruction-following ability, but adapting them to diverse visual-language domain

local-aiarxiv-cs-cv

Distributed Optimization with Streaming Data: A Temporal Weighting Perspective

arXiv:2608.09565v1 Announce Type: cross Abstract: Optimization theory is a widely used tool for intelligent decision-making. While classical optimization deals with fixed, time-invariant objective fun

Distribution-Free Conformal Prediction for Steel Fatigue Strength: Marginal Validity Is Not Enough

arXiv:2608.07589v1 Announce Type: cross Abstract: Predicting fatigue failure in steel components experimentally is costly because it requires testing across multiple compositions and processing condit

safetyarxiv-cs-lg

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

arXiv:2608.09047v1 Announce Type: cross Abstract: Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very l

Do AI Forecast Ensembles Sample the Correct Conditional Distribution?

arXiv:2608.08954v1 Announce Type: cross Abstract: Ensemble forecasting aims to sample the conditional distribution of outcomes; whether AI forecast ensembles do this correctly in a joint sense remains

Do All LLMs Know When They're Being Harmful? A Reproducibility Study of Latent-Space Safety Probes Across Model Families

arXiv:2608.08029v1 Announce Type: cross Abstract: Khatri et al. (2026) [DOI: 10.1109/DSN-W70714.2026.00027] show that lightweight MLP probes on final-layer activations of a single 8B model (LLaMA-3.1-

Do Evaluation Metrics Detect Errors in Classical Chinese to English Translations?

arXiv:2608.08283v1 Announce Type: cross Abstract: Although large language models can translate some historical languages surprisingly well, their usefulness in digital humanities workflows is limited

DocAtlas: Long-Document Understanding as Mutable-State Interaction

arXiv:2608.07527v1 Announce Type: cross Abstract: Long-document understanding requires models to find and combine evidence across many pages, layouts, tables, figures, and charts. Existing retrieval-a

DocPure: Prompt-Free Unified Document Restoration via Degradation-Aware Structure-Guided Wavelet Modulation

arXiv:2608.09536v1 Announce Type: new Abstract: High-quality document images are pivotal for information archiving and downstream automatic processing. However, they are frequently compromised by dive