Search: “framework”

OPLD: On-Policy Latent Distillation for Multimodal Reasoning

arXiv:2607.28154v1 Announce Type: new Abstract: Interleaved multimodal Chain-of-Thought (CoT) improves visual reasoning by incorporating auxiliary visual evidence into intermediate reasoning. However,

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PlatformBid: An Auto-Bidding Benchmark from a Unified Advertising Platform's Perspective

DGX agent

arXiv:2607.27265v1 Announce Type: new Abstract: Real-time bidding is central to computational advertising, comprising three elements: Supply Side Platform (SSP) selling ad impressions, Demand Side Pla

model-releasesarxiv-cs-lg

31 Jul 2026

PrintAnything: Learning an Intermediate Representation for 3D printing G-code Generation

arXiv:2607.27729v1 Announce Type: new Abstract: Point clouds are one of the most fundamental and widely used 3D representations, serving as the most basic geometric representation of 3D shapes. Nevert

Private Face Recognition Training Dataset Publication via Identity-Decoupled and Geometry-Preserving Face Distillation

arXiv:2607.27764v1 Announce Type: new Abstract: Publishing private face recognition~(FR) training datasets is privacy-sensitive because faces expose identity information. Private FR training dataset p

Procedural Fairness in Multi-Agent Bandits

arXiv:2601.10600v2 Announce Type: replace-cross Abstract: In the context of multi-agent multi-armed bandits (MA-MAB), fairness is often reduced to outcomes: maximizing welfare, reducing inequality, or

Prox: Training-Free FFN Activation Sparsity via Approximate Intermediate-Channel Salience in LLMs

arXiv:2607.27591v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate memory traffic and computation in large language model (LLM) inference, making them a primary target for activat

researcharxiv-cs-cl

QuantWAMs: Calibrating at the Right Granularity for World Action Models

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

RaDiVe: Robust 4D Radar Odometry with Distance-Bounded NDT and Velocity-Discrepancy Point Uncertainty

arXiv:2607.28045v1 Announce Type: new Abstract: Recent advances in 4D radar enable robust perception in adverse weather; however, the inherent sparsity, noise, and limited positional precision of rada

researcharxiv-cs-ro

Random Projection Flows for Efficient Manifold Density Estimation

arXiv:2509.25228v3 Announce Type: replace Abstract: Accurate density estimation is crucial for understanding complex high-dimensional data, but it becomes challenging when the data lies on or near low

Real-Time Hard Peak Age-of-Information Safety with No-Regret Learning

arXiv:2607.27626v1 Announce Type: new Abstract: Safety-critical IoT systems such as industrial closed-loop control, V2X coordination, and remote teleoperation require every sensor's peak Age of Inform

RedFlow: Redirect Failure into Action-Level Corrections for Flow-matching VLA Policy

model-releasesarxiv-cs-ro

arXiv:2607.27782v1 Announce Type: new Abstract: Flow-matching Vision-Language-Action (VLA) policies have shown strong potential for robotic manipulation but often suffer from compounding errors caused

Tutorials

ReDiff: Reliability-Guided Diffusion for Trustworthy Ultra-Low-Field to High-Field MRI Synthesis

arXiv:2603.11325v2 Announce Type: replace Abstract: Low-field to high-field MRI synthesis has emerged as a promising strategy to improve image quality when access to high-field scanners is limited. Ho

tutorialsarxiv-cs-cv

ReDiPPO: Reference-Guided Value Calibration and Discrepancy-Aware Token Reweighting for Mathematical Reasoning

arXiv:2607.27631v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for enhancing the mathematical reasoning capabilities of large language models. Among exis

safetyarxiv-cs-cl

REFINE-DP: Diffusion Policy Fine-tuning for Humanoid Loco-manipulation via Reinforcement Learning

arXiv:2603.13707v3 Announce Type: replace-cross Abstract: Humanoid loco-manipulation requires coordinated task-space motion planning with stable loco-manipulation command tracking under complex robot-

Rethinking EEG-Based Disease Diagnosis: Decoupling Instance Representation Learning from Subject-Level Supervision

arXiv:2607.27274v1 Announce Type: new Abstract: EEG-based disease diagnosis requires one prediction per subject, yet common pipelines segment recordings into short instances, inherit the subject label

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

arXiv:2607.28581v1 Announce Type: new Abstract: High-fidelity 3D generation predominantly relies on scaling model capacity and data, which incurs prohibitive computational costs. This paradigm typical

Robust Wavelength Selection for Partial Least Squares Sugar Content Estimation Using Combinatorial Bayesian Optimization

arXiv:2607.27645v1 Announce Type: cross Abstract: Wavelength selection is one of the important preprocessing methods in near-infrared spectroscopy to improve prediction accuracy and interpretability o

RRM: Experience-Driven Reflective Retrieval Memory for Long-Horizon Multimodal Reasoning

arXiv:2607.28156v1 Announce Type: new Abstract: Existing multimodal long-term memory agents use external memory to overcome the limited context available for long videos. However, most methods emphasi

researcharxiv-cs-cl

SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation

model-releasesarxiv-cs-ai

arXiv:2607.26313v1 Announce Type: cross Abstract: Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are

Scaling medical imaging report generation with multimodal reinforcement learning

model-releasesarxiv-cs-cl

arXiv:2601.17151v2 Announce Type: replace-cross Abstract: Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit ma

SDO: Structure-Aware Data Organization for Efficient LLM Post-Training

arXiv:2607.27273v1 Announce Type: new Abstract: Post-training of large language models is expensive, and existing efficiency improvements mainly focus on selecting informative samples or designing tra

SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups

arXiv:2607.27431v1 Announce Type: new Abstract: Generative modeling of protein backbones promises the de novo design of proteins with prescribed structural and functional properties. Existing diffusio

Search Strategies for Optimal Classification and Regression Trees

arXiv:2607.28170v1 Announce Type: new Abstract: Optimal decision trees (ODTs) are compact, interpretable machine learning models that globally optimize a given objective, but their scalability remains

SemAnCorr: Semantic Anchored Correspondence for Zero-Shot Manipulation Skill Transfer

model-releasesarxiv-cs-ro

arXiv:2607.28382v1 Announce Type: new Abstract: Transferring manipulation skills across object instances that share functionality but differ in geometry remains a fundamental challenge in robot learni

Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis

arXiv:2607.27790v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) aims to interpret complex human emotions by integrating natural language with non-verbal modalities. Non-verbal moda

researcharxiv-cs-cl

Shared Symbolic Backbones for Physically Consistent Multi-Output Symbolic Regression

model-releasesarxiv-cs-ai

arXiv:2607.26528v1 Announce Type: cross Abstract: Symbolic regression provides analytical expressions, but it is usually applied one output at a time. This is limiting in process systems, where state

Sign Language Question Answering: A New Task, Benchmark, and Baseline for Sign Language Understanding

arXiv:2607.27826v1 Announce Type: cross Abstract: Recent advances in sign language (SL) understanding (SLU) have led to remarkable progress in tasks such as continuous SL recognition and SL translatio

Simplifying Neural Networks During Training

arXiv:2607.27854v1 Announce Type: cross Abstract: Understanding and exploiting the training dynamics of overparameterized deep neural networks remains a central challenge in modern machine learning. R

SkillSight: Calibrating Generic Content Bias for Skill Retrieval

arXiv:2607.18785v2 Announce Type: replace Abstract: As large language model agents gain access to increasingly large skill libraries, retrieving the right skill becomes critical to reliable capability

safetyarxiv-cs-ai

Agents

SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge

arXiv:2607.27497v1 Announce Type: new Abstract: Agentic systems driven by large language models (LLMs) regularly feature two key mechanisms to autonomously solve complex problems: synthesizing text-ba

agentsarxiv-cs-cl

SPFM-Net: Semantic-Prior-Guided Frequency-Constrained Mamba for Invisible Watermark Attack

arXiv:2607.27811v1 Announce Type: new Abstract: Existing watermark attacks typically rely on predefined signal-processing operations or locally constrained restoration networks, making it difficult to

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

arXiv:2603.15684v2 Announce Type: replace-cross Abstract: Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although

safetyarxiv-cs-ai

STEREODISCO: Discovering Stereotypicality in LLMs

model-releasesarxiv-cs-lg

arXiv:2607.27824v1 Announce Type: cross Abstract: LLMs encode, convey, and perpetuate stereotypes. Prior computational research focuses on a small set of semantic axes investigated in social psycholog

SVR: Self-Verifying Refinement via Joint Verdict-Confidence Reinforcement Learning for Adaptive Test-Time Compute

arXiv:2607.28457v1 Announce Type: cross Abstract: Scaling test-time computation can improve language-model reasoning, but uniform budgets waste computation on easy inputs, while verifier-guided refine

safetyarxiv-cs-cl

TAPO: Transition-Aware Policy Optimization for LLM Agents

arXiv:2607.27973v1 Announce Type: new Abstract: Recently, Reinforcement Learning (RL) has emerged as a crucial paradigm for the post-training of Large Language Model (LLM) agents. However, existing me

Temporal Concentration from Rollout Errors: Implicit Preference Optimization for Text-to-Video Diffusion

arXiv:2607.28058v1 Announce Type: new Abstract: Recent advances in preference alignment for diffusion-based video generation, particularly via Direct Preference Optimization (DPO), have significantly

Agents

The Role of Causality in Algorithmic Recourse

arXiv:2607.28497v1 Announce Type: new Abstract: Algorithmic recourse aims to provide individuals with actionable changes to improve their predicted outcomes in high-stakes classification settings, suc

agentsarxiv-cs-lg

Theatre Chapbooks At Scale: A Statistical Comparative Analysis of Typography

arXiv:2607.27266v1 Announce Type: new Abstract: We propose a statistical methodology that quantifies the similarity of typefaces between printed historical books. This provides a tool that accelerates

Theia: Large-Scale Multimodal Captioning and Automated Validation of the Incidents1M Dataset for Data-Free Distillation

arXiv:2607.28269v1 Announce Type: new Abstract: The deployment of Vision-Language Models (VLMs) in critical domains like disaster management requires high-quality multimodal datasets, especially for t

THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model

model-releasesarxiv-cs-cl

arXiv:2607.27303v1 Announce Type: cross Abstract: Temporal heterogeneous graphs offer a natural abstraction for dynamic relational systems in which diverse node and relation types co-exist and evolve

Three-Photon Bayesian Imaging of Ortho-Positronium

arXiv:2607.27741v1 Announce Type: cross Abstract: PET provides functional images relying on two-photon coincidences from positron-electron annihilation. In human tissue, about 40% of annihilations are

TongueReenact: Geometry-Anchored Tongue Synthesis for Face Reenactment

arXiv:2607.28039v1 Announce Type: new Abstract: Modern face reenactment systems achieve impressive pose and expression transfer using geometry-driven representations. However, they largely ignore tong

Tutorials

Towards Robust Monocular Depth Estimation in Non-Lambertian Surfaces

arXiv:2408.06083v2 Announce Type: replace Abstract: In the field of monocular depth estimation (MDE), many models with excellent zero-shot performance in general scenes emerge recently. However, these

tutorialsarxiv-cs-cv

Towards Unified Multimodal Misinformation Detection in Social Media: A Benchmark Dataset and Baseline

arXiv:2509.25991v3 Announce Type: replace-cross Abstract: Detecting deceptive multimodal content on social media has become an increasingly important problem. Two major types of deception dominate: hu

TSOG: A Format For Temporally And Spatially Ordered Gaussians

arXiv:2607.28049v1 Announce Type: cross Abstract: We propose Temporally and Spatially Ordered Gaussians (TSOG), a format for efficient representation of 4D Gaussian Splatting (4DGS) content. TSOG exte

Uncertainty quantification for trustworthy deep learning: Methods and measures

arXiv:2607.28248v1 Announce Type: cross Abstract: The deployment of deep neural networks in safety-critical domains demands reliable estimates of predictive confidence, yet conventional architectures

Unifying Adversarially Robust Model Experts in Vision-Language Models

arXiv:2607.27897v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, are vulnerable to adversarial attacks, posing a serious problem for real-life applications and deployment.

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards

arXiv:2511.23310v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective paradigm for post-training large language models, yet the de