Search: “models”

When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning

arXiv:2608.02940v1 Announce Type: new Abstract: A reproducible compression statistic can still select the wrong candidate. A dense pruning score with 0.906 split-half reliability predicted a 16.1% gai

local-aiarxiv-cs-ai

5 Aug 2026

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Safety

When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation

DGX agent

arXiv:2608.03342v1 Announce Type: cross Abstract: Conditional segmentation models may be trained and evaluated with auxiliary signals cleaner than those available at deployment. We study this protocol

safetyarxiv-cs-ai

5 Aug 2026

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation

arXiv:2608.03632v1 Announce Type: new Abstract: On-Policy distillation (OPD) transfers teacher capabilities by supervising student-sampled trajectories with dense token-level teacher signals. Recent s

safetyarxiv-cs-ai

5 Aug 2026

3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning

arXiv:2510.03011v2 Announce Type: replace Abstract: Diffusion models have shown strong potential for robot skill learning, yet their role in coverage path planning remains underexplored. In industrial

safetyarxiv-cs-ro

3DZip: Spatial-Aware Feature Diversity-Guided Token Compression for 3D Question Answering

arXiv:2608.01185v1 Announce Type: new Abstract: Recent 3D vision-language models (3D VLMs) construct geometry aware tokens by projecting 2D visual features into world coordinates, enabling spatial rea

Agents

Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning

arXiv:2608.00301v1 Announce Type: cross Abstract: Error-penalized scoring rules (+1 for a correct answer, -lambda for a wrong one, 0 for abstaining) are increasingly prescribed against hallucination:

agentsarxiv-cs-cl

Assessing the Impacts of Imperfect Datasets on Client Selections in Federated Learning

arXiv:2608.02250v1 Announce Type: new Abstract: Federated learning (FL) is a popular distributed learning framework where multiple clients perform local training and a server aggregates the locally up

local-aiarxiv-cs-lg

Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization

arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical findi

Benign Overfitting in Linear Classifiers with a Bias Term

arXiv:2511.12840v2 Announce Type: replace-cross Abstract: Overparameterized models often generalize well even when they interpolate noisy training data. This is known as benign overfitting. For linear

Breaking the Statistical Similarity Trap in Extreme Convection Detection

arXiv:2509.09195v2 Announce Type: replace-cross Abstract: Current evaluation metrics for deep learning weather models create a 'Statistical Similarity Trap', rewarding blurry predictions while missing

safetyarxiv-cs-cv

Agents

Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation

arXiv:2608.02345v1 Announce Type: new Abstract: A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering e

agentsarxiv-cs-cl

CascadeLUT: Information-Ordered Streaming Inference for Bandwidth-Constrained FPGAs

arXiv:2608.00720v1 Announce Type: cross Abstract: Mapping neural networks to FPGAs enables low-latency, energy-efficient inference, particularly for lookup table (LUT)-based models that eliminate mult

local-aiarxiv-cs-lg

Coverage-Driven Adaptive Keyframe Selection for Video Understanding

arXiv:2608.00714v1 Announce Type: new Abstract: Recent advances in large vision-language models (LVLMs) have enabled long-video understanding and analysis. However, processing the large number of fram

tutorialsarxiv-cs-cv

CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs

arXiv:2608.02578v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing th

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception

arXiv:2608.01055v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly expected to solve structured perception tasks that require visual recognition, language-to-obj

Cultural Awareness is Represented but Not Decoded: Tracing Mythological Knowledge across 18 Open-Source LLMs

arXiv:2608.02486v1 Announce Type: new Abstract: Open-source LLMs reliably name Zeus, Jupiter, and Thor, but recover their counterparts in less-represented traditions like Finnish, Slavic, Egyptian, or

D^2-4DGS: Dual-Depth Guided Sparse-Camera 4D Gaussian Splatting

arXiv:2608.01588v1 Announce Type: new Abstract: Dynamic 4D Gaussian Splatting has emerged as an efficient representation for dynamic novel view synthesis through explicit scene modeling and real-time

Decisions over Sequences: Computability and Choice

arXiv:2203.00070v3 Announce Type: replace-cross Abstract: We develop a framework to study situations where decision makers face alternatives sequentially. Within this framework, we focus on endogenous

Deep Research Pretraining via Predictive Navigation

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

safetyarxiv-cs-cl

DeepDefense: Robust Learning via Layer-Wise Gradient-Feature Alignment

arXiv:2511.13749v2 Announce Type: replace Abstract: Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predi

Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them

arXiv:2608.01402v1 Announce Type: new Abstract: We address the problem of understanding when and why Vision-Language-Action models struggle with contact-rich manipulation tasks that require precise ph

safetyarxiv-cs-ro

Detecting Nonproperness of Likelihood Equations

arXiv:2608.01976v1 Announce Type: cross Abstract: Given an algebraic statistical model, a challenging problem is classifying the data according to the number of positive critical points of the likelih

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

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

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

Applications

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

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

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

Exploiting Intrinsic Duality for Multi-Hop Question Generation

arXiv:2608.00712v1 Announce Type: new Abstract: Multi hop question generation (MQG) aims to generate questions from multiple given documents and target answers, whereas question answering (QA) focuses

safetyarxiv-cs-cl

Agents

FactorJEPA: Factorizing Monolithic Futures into Layout-Agent-Interaction Channels for Crowded and Chaotic Global South Urban Worlds

arXiv:2608.01049v1 Announce Type: cross Abstract: World models have attracted significant attention for their ability to capture and predict the structure and dynamics of the physical world. In this e

agentsarxiv-cs-cv

FAST-GS: Frequency Aware Space-time Gaussian Splatting for Photorealistic Dynamic Novel View Synthesis

arXiv:2608.01958v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) excels in dynamic 3D reconstruction and real-time novel view synthesis via efficient 4D Gaussian representations and parall

local-aiarxiv-cs-cv

FAU at ImageCLEF 2026 Task on Multimodal Reasoning Robust Candidate Scoring and Concise Multilingual Visual Answering

arXiv:2608.01664v1 Announce Type: new Abstract: We present our ImageCLEF 2026 Multimodal Reasoning system for the Visual Multiple Choice Question Answering (Visual MCQ) and Visual Open Question Answer

From Chains to Trees: Parent-Conditioned Drafting for Semi-Autoregressive Speculative Decoding

arXiv:2608.02123v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference only when drafted continuations survive target-model verification. Semi-autoregressive drafters such as D

From fragmented data to actionable design: Physics-calibrated learning for plastic upcycling

arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco

From Pixels to PCells: A Neurosymbolic Approach to Photonic Component Creation

arXiv:2608.00084v1 Announce Type: new Abstract: We present PixCell, a neurosymbolic system in which multimodal agents convert a visually presented photonic component into a parametric program over a s

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

tutorialsarxiv-cs-cv

Gimbal360: Canonicalizing Planar Diffusion for Spherical Panorama Completion

arXiv:2603.23179v2 Announce Type: replace Abstract: Diffusion models provide powerful priors for 2D image completion, but these priors are learned on bounded planar images and do not transfer directly

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees

safetyarxiv-cs-ro

HiResNets: Native Full-HD Video Recognition with Foveal Residual Streams

arXiv:2608.02140v1 Announce Type: new Abstract: Much of the recent progress in image and video recognition has come at the cost of memory: larger models, increased resolution, and longer temporal cont

tutorialsarxiv-cs-cv

Hybrid Quantum CNN for Cross-Sensor Spaceborne Volcanic Thermal Activity Recognition Worldwide

arXiv:2608.00069v1 Announce Type: cross Abstract: As Earth Observation (EO) enters the Big Data era, the exponential volume of daily satellite imagery poses significant computational and storage chall

InstancePin: Instance-Addressable Layout-to-Image Diffusion via Coordinate Pinning

arXiv:2608.00588v1 Announce Type: new Abstract: Layout-to-image diffusion models have achieved impressive semantic controllability by conditioning generation on category-level segmentation maps. Howev

Latent-Regime Bias Auditing for Volatility Forecasting

arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m

Latent Softmax for Data-Efficient Phoneme-Based Multilingual ASR Across Tonal and Non-Tonal Languages

arXiv:2608.01281v1 Announce Type: cross Abstract: Phoneme-based multilingual automatic speech recognition (ASR) can share acoustic evidence across languages more directly than language-specific subwor

LEAP: Lean Environment-Feedback via Adaptive Pruning for Code RL in GPU Kernel Generation

arXiv:2608.01804v1 Announce Type: new Abstract: Post-training large language models (LLMs) via reinforcement learning (RL) has significantly advanced code generation capabilities. To bypass the heavy

Learning-Based Collaborative MEC for LLM Inference with Soft-Deadline Awareness via Transformer-Enhanced PPO

arXiv:2608.02031v1 Announce Type: cross Abstract: This paper investigates collaborative mobile edge computing (MEC) servers for large language model (LLM) inference under soft deadline constraints. In

Learning to Persuade Privately Informed Receivers

arXiv:2607.28342v1 Announce Type: cross Abstract: Bayesian persuasion studies how an informed sender can influence the behavior of a receiver through strategic information disclosure. Standard models