Search: “models”

PHF: Privileged Hidden Flow for On-Policy Self-Distillation

arXiv:2606.29340v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees veri

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Preserving Fairness and Safety in Quantized LLMs Through Critical Weight Protection

DGX agent

arXiv:2601.12033v2 Announce Type: replace Abstract: Quantization is widely adopted to reduce the computational cost of large language models (LLMs); however, its implications for fairness and safety,

safetyarxiv-cs-cl

30 Jun 2026

Agents

Preventing Error Propagation in Multi-Agent AI through Runtime Monitoring

arXiv:2606.29026v1 Announce Type: new Abstract: Multi-agent AI systems can improve answer selection by allowing different language models to exchange reasoning traces, revise initial predictions, and

agentsarxiv-cs-ai

Projection-based coupling of infrared thermography and stereocorrelation-based digital image correlation

arXiv:2606.28905v1 Announce Type: new Abstract: Full-field measurement techniques such as digital image correlation and infrared thermography are prevalent in experimental solid mechanics. Digital ima

Propagation of~Interval Belief Structures and~Imprecise Copulas for~Neural Network Verification

arXiv:2606.30105v1 Announce Type: new Abstract: Quantitative verification of neural networks requires reasoning about probabilities under substantial uncertainty in both input distributions and their

ProSpec RL: Plan Ahead, then Execute

arXiv:2407.21359v2 Announce Type: replace-cross Abstract: Imagining potential outcomes of actions before execution helps agents make more informed decisions, a prospective thinking ability fundamental

PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking

arXiv:2606.30476v1 Announce Type: new Abstract: We introduce Point-supervised Multi-Object Tracking (PS-MOT) as a cost-effective alternative to traditional bounding box supervision, shifting the focus

PS-PPO: Prefix-Sampling PPO for Critic-Free RLHF

arXiv:2606.29758v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) for Large Language Models increasingly relies on critic-free methods as a practical alternative to a

Local Ai

RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs

arXiv:2606.29855v1 Announce Type: new Abstract: In precipitation forecasting, not only accuracy but also temporal resolution is critical. However, increasing temporal resolution is constrained by obse

local-aiarxiv-cs-cv

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

arXiv:2606.30362v1 Announce Type: cross Abstract: While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a res

RefGlass-GS: A UAV-Enabled Fusion Framework for Photorealistic, Semantic and Interactive Digitization of Reflective Glass Facades via Gaussian Splatting

arXiv:2606.28826v1 Announce Type: new Abstract: Existing digitization of buildings with reflective glass facades suffers from geometric reconstruction distortion, unrealistic view-dependent texture re

applicationsarxiv-cs-cv

Reproducing FACTER: Fairness via Conformal Thresholding and Prompt Repair

arXiv:2606.28620v1 Announce Type: cross Abstract: Fayyazi et al. (2025) recently proposed FACTER, a model-agnostic framework designed to jointly enforce fairness and statistical coverage in LLM-based

safetyarxiv-cs-lg

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors

arXiv:2606.29428v1 Announce Type: new Abstract: Zero-shot anomaly detection aims to identify defects in arbitrary novel domains; however, existing models assume that the auxiliary data contains a rich

SA-VIS: Sparse frame Annotations for training Video Instance Segmentation

arXiv:2606.20140v2 Announce Type: replace Abstract: Recent online video instance segmentation (VIS) methods have achieved impressive results, thus becoming the preferred approach to segment instances

Same Concept, Different Directions: Cross-Modal Feature Heterogeneity in Sparse Autoencoders

arXiv:2606.29888v1 Announce Type: cross Abstract: Vision-language models map images and text into a joint embedding space. However, these embeddings often entangle multiple semantic features, which li

Sample-Efficient Learning of Probabilistic Causes for Reachability in Markov Decision Processes with Probabilistic Guarantees

arXiv:2606.29681v1 Announce Type: new Abstract: Probabilistic model checking for Markov decision processes (MDPs) provides quantitative guarantees, but often offers limited insight into why undesired

SARLO-80: Worldwide Slant SAR Language Optic Dataset 80cm

arXiv:2606.20523v2 Announce Type: replace-cross Abstract: Multimodal foundation models have advanced rapidly thanks to large optical benchmarks, but comparable resources for synthetic aperture radar (

Tutorials

ScaleErasure: Inference-Time Minimal Intervention for Precise Concept Erasure in Next-Scale Autoregressive Image Generation

arXiv:2606.29282v1 Announce Type: new Abstract: Concept erasure aims to prevent image generative models from producing unsafe content while preserving their general generative capability. Meanwhile, n

tutorialsarxiv-cs-cv

Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics

arXiv:2606.28387v1 Announce Type: cross Abstract: Enterprise text-to-SQL systems often fail before SQL is generated: the model receives the wrong schema context. Modern warehouses contain thousands of

applicationsarxiv-cs-ai

Local Ai

See Only When Needed: Context-Aware Attention Intervention for Mitigating Hallucinations in LVLMs

arXiv:2606.29847v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) excel at multimodal tasks but remain prone to object hallucinations. Prior training-free remedies often uniformly s

local-aiarxiv-cs-cv

SemConFlow: Semantic Grounding of Holistic Co-Speech Gesture Generation with Contrastive Flow-Matching

arXiv:2603.26553v2 Announce Type: replace Abstract: While the field of co-speech gesture generation has seen significant advances, producing holistic, semantically grounded gestures remains a challeng

Sequential Fairness Auditing with Limited Output Access

arXiv:2606.30338v1 Announce Type: new Abstract: External evaluations are becoming increasingly central to the governance of AI systems. In practice, however, independent auditors often have limited ac

SPARC: Scalable Path-Specific Counterfactual Fairness via Causal Conditional Independence

arXiv:2412.04739v2 Announce Type: replace Abstract: Deep learning models exhibit fairness concerns when predictions are inadvertently influenced by sensitive attributes. However, existing attempts to

Speculative Pre-Positioning: Decoding Stateful Sessions to the Next Decision Point Off the Critical Path

arXiv:2606.29565v1 Announce Type: new Abstract: A stateless inference server (vLLM, SGLang, TensorRT-LLM) idles between requests while the accelerator waits; a stateful session reclaims that idle time

researcharxiv-cs-lg

T3R: Deeper Test-Time Adaptation for Graph Neural Networks via Gradient Rotation

arXiv:2606.30011v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) deployed in real-world systems typically have fixed weights, often leading to degraded performance under distribution shi

applicationsarxiv-cs-ai

Tactile Gesture Recognition with Built-in Joint Sensors for Industrial Robots

arXiv:2508.12435v2 Announce Type: replace-cross Abstract: While gesture recognition using vision or robot skins is an active research area in Human-Robot Collaboration (HRC), this paper explores deep

TerraDiT: Point-Conditioned Diffusion Transformer for Satellite Image Synthesis

arXiv:2603.02172v2 Announce Type: replace Abstract: We introduce TerraDiT, a diffusion transformer designed for text-to-satellite image generation with point-based control. Existing controlled satelli

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives

arXiv:2510.06096v3 Announce Type: replace-cross Abstract: The objectives that Large Language Models (LLMs) implicitly optimize remain dangerously opaque, making trustworthy alignment and auditing a gr

safetyarxiv-cs-cl

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks

arXiv:2606.28529v1 Announce Type: cross Abstract: Embodied foundation models have recently been widely used to improve robot generalization and task success rates. Previous works apply lossy efficient

ThinkProbe: Beyond Accuracy -- Structural Profiling of Open-Ended LLM Reasoning Traces via Non-Generative Thought Graphs

arXiv:2606.29067v1 Announce Type: new Abstract: We present ThinkProbe, a framework for structural analysis of LLM reasoning traces. ThinkProbe converts each trace into a Thought Graph a directed graph

researcharxiv-cs-cl

Timesteps of Mamba Align with Human Reading Times

arXiv:2606.29904v1 Announce Type: new Abstract: This study demonstrates an alignment of per-word processing time in a popular state-space language model Mamba and human readers. In Mamba, the recurren

safetyarxiv-cs-cl

To Reason or to Fabricate: Reasoning Without Shortcuts via Hint-Anchored Pairwise Aggregation

arXiv:2606.29481v1 Announce Type: cross Abstract: While reinforcement learning (RL) significantly enhances LLM reasoning, its efficacy is severely undermined by Pre-RL data overlap, where RL datasets

Hardware

Transolver-3: Scaling Up Transformer Solvers to Industrial-Scale Geometries

arXiv:2602.04940v2 Announce Type: replace Abstract: Deep learning has emerged as a transformative tool for the neural surrogate modeling of partial differential equations (PDEs), known as neural PDE s

hardwarearxiv-cs-lg

Two-Stage Prompt Optimization for Few-Shot Relation Extraction: From Reasoning-Guided Search to Gradient-Guided Refinement

arXiv:2606.29639v1 Announce Type: cross Abstract: Automatic prompt optimization is still underexplored for episodic few-shot relation extraction with smaller language models. We propose a two-stage fr

Uncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation

arXiv:2606.30395v1 Announce Type: cross Abstract: Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic informat

safetyarxiv-cs-cl

Understanding LLM Intervention Explanations in Multi-Party Human-Robot Interaction

arXiv:2606.29460v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly embedded in social robots to support natural group interactions, yet their role in complex multi-party set

researcharxiv-cs-ro

VISTA-DZ: Visual Semantic Trajectory Adaptation for Personalized Dilemma Zone Prediction

arXiv:2606.29548v1 Announce Type: cross Abstract: Driver decision making in the dilemma zone at signalized intersections is safety critical, as vehicles approaching a yellow signal must decide whether

W4A4 Quantization for Inference on Wan2.2-I2V-A14B

arXiv:2606.29337v1 Announce Type: new Abstract: We summarize our submission to Sub-Challenge 1: W4A4 Quantization for Inference (HiF4 / MXFP4) of the ICME 2026 Low-Bit-width Large-Model Quantization C

When Does Sparsity Mitigate the Curse of Depth in LLMs

arXiv:2603.15389v2 Announce Type: replace Abstract: Recent work has demonstrated the curse of depth in large language models (LLMs), where later layers contribute less to learning and representation t

researcharxiv-cs-cl

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate

arXiv:2512.03578v3 Announce Type: replace-cross Abstract: Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series. It appears in

applicationsarxiv-cs-ai

Agents

When LLMs Develop Languages: Symbolic Communication for Efficient Multi-Agent Reasoning

arXiv:2606.29354v1 Announce Type: new Abstract: Chain-of-Thought (CoT) improves large language models (LLMs) on difficult reasoning tasks, but it often incurs long natural-language rationales that are

agentsarxiv-cs-ai

X-Morph: Human Motion Priors for Scalable Robot Learning Across Morphologies

arXiv:2606.30290v1 Announce Type: new Abstract: Recent progress in humanoid behavior models has been driven in large part by abundant human motion data, but comparable motion data is scarce for non-hu

safetyarxiv-cs-ro

Zero-Label Driving Scenario Complexity Detection via Joint Embedding Predictive Architecture

arXiv:2606.28383v1 Announce Type: new Abstract: Identifying complex and safety-critical driving scenarios in large unlabelled datasets is an important but expensive problem. Existing approaches rely o

A Survey of Automated Presentation Coaching: Systems, Methods, and Open Challenges

arXiv:2606.27380v1 Announce Type: new Abstract: Automated coaching for oral presentations sits at the intersection of computer-assisted pronunciation training (CAPT), prosody modeling, and speech synt

researcharxiv-cs-cl

Active Exploration via Autoregressive Generation of Missing Data

arXiv:2405.19466v4 Announce Type: replace Abstract: We pose uncertainty quantification and exploration in online decision-making as a problem of training and generation from an autoregressive sequence

researcharxiv-cs-lg

An Embedded Real-Time License Plate Recognition System for Complex Traffic Scenes

arXiv:2606.27772v1 Announce Type: new Abstract: Vehicle license plate recognition is an integral component of intelligent transportation systems. In this work, we present an embedded real-time license

Boundary condition fidelity for bottom-hole pressure and CO2 plume prediction in geological carbon storage

arXiv:2606.27515v1 Announce Type: new Abstract: Accurate prediction of bottom-hole pressure (BHP) and CO2 plume migration is essential for safe geological carbon storage, yet practical simulations oft

researcharxiv-cs-lg

Local Ai

CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detection

arXiv:2504.01882v2 Announce Type: replace Abstract: The use of DNS over HTTPS (DoH) tunneling by an attacker to hide malicious activity within encrypted DNS traffic poses a serious threat to network s

local-aiarxiv-cs-lg