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JustDepth: Real-Time Radar-Camera Depth Estimation with Single-Scan LiDAR Supervision

arXiv:2607.22172v1 Announce Type: new Abstract: Accurate yet low-latency depth is essential for radar-camera perception in autonomous systems. Cameras provide rich appearance but lack metric scale, wh

agentsarxiv-cs-cv

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k{appa}-LoRA: Condition Numbers Reveal Which LoRA Matrices Worth Updating

DGX agent

arXiv:2607.22489v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become a widely adopted technique for efficient neural network fine-tuning, decomposing model updates into low-rank matri

model-releasesarxiv-cs-lg

27 Jul 2026

Khondo: A Multimodal Benchmark for Document Packet Splitting of Bangla Forms

arXiv:2607.21780v1 Announce Type: new Abstract: Document packets, multiple documents concatenated into a single file, are common in government and administrative workflows, yet splitting them into the

Language-Aware Distillation for Multilingual Instruction-Following Speech LLMs with ASR-Only Supervision

arXiv:2603.07025v2 Announce Type: replace Abstract: Speech Large Language Models (LLMs) that understand and follow instructions in many languages are useful for real-world interaction, but are difficu

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

arXiv:2508.13826v4 Announce Type: replace-cross Abstract: Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limit

Latent PDE mapping for efficient physics-informed learning across geometries with limited data

arXiv:2607.22215v1 Announce Type: new Abstract: In this study, we introduce latent PDE mapping, a broadly applicable physics-informed learning technique designed to enable efficient geometric generali

LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks

arXiv:2607.21941v1 Announce Type: new Abstract: Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and

Layer-wise LoRA fine-tuning: a similarity metric approach

arXiv:2602.05988v2 Announce Type: replace Abstract: Pre-training Large Language Models (LLMs) on web-scale datasets becomes fundamental for advancing general-purpose AI. In contrast, enhancing their p

LayoutLite: Token-Level Implicit Layout Analysis for Efficient Document OCR

arXiv:2607.22200v1 Announce Type: new Abstract: End-to-end OCR systems based on vision-language models have achieved strong performance in complex document OCR, but their efficiency is limited by the

safetyarxiv-cs-cv

LeAct: Learning to Reason from Expert Actions

arXiv:2607.21856v1 Announce Type: cross Abstract: Modern reasoning models depend on reasoning data, today sourced from human annotations or distilled from stronger LLMs. However, a rich and largely un

Tutorials

Learning Adaptive Semantic Gaussian Allocation for 3D Occupancy

arXiv:2607.21896v1 Announce Type: new Abstract: Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under v

tutorialsarxiv-cs-cv

Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks

arXiv:2607.22313v1 Announce Type: cross Abstract: Estimating contemporaneous bidirectional interactions from observational data is difficult because each outcome is endogenous to the other, while flex

agentsarxiv-cs-lg

Tutorials

Learning Diverse Humanoid Tasks via Synthetic Video Scenarios without Real World Data

arXiv:2607.21648v1 Announce Type: new Abstract: The human-like morphology of humanoid robots grants them exceptional potential for agile and versatile motor capabilities, but it also introduces signif

tutorialsarxiv-cs-ro

Learning Ergodic Dynamical Systems from a Finite Trajectory

arXiv:2607.22399v1 Announce Type: cross Abstract: We consider the problem of learning from a single finite trajectory of an ergodic stochastic dynamical system. More precisely, we study discrete-time

agentsarxiv-cs-lg

Learning Spatiotemporal Decision Priors for Efficient Path Planning under Partial Observability

arXiv:2607.22166v1 Announce Type: new Abstract: Path planning under partial observability remains challenging because an agent must make long-horizon navigation decisions from only locally bounded obs

safetyarxiv-cs-ro

Tutorials

Learning to Reason for Factuality

arXiv:2508.05618v2 Announce Type: replace Abstract: Reasoning Large Language Models (R-LLMs) have significantly advanced complex reasoning tasks but often struggle with factuality, generating substant

tutorialsarxiv-cs-cl

Learning What Matters: Supervising Sparse Attention Routing with Causal Evidence Sets

arXiv:2607.21692v1 Announce Type: cross Abstract: Sparse attention reduces the cost of long contexts by allowing each query to read only selected parts of the input. These selectors are often trained

Local Ai

Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models

arXiv:2607.21936v1 Announce Type: new Abstract: Historical documents act as invaluable knowledge archives but often suffer from illegibility due to physical deterioration and damage. While existing re

local-aiarxiv-cs-cl

LLM-Based Visual Explanation Evaluation Framework for Assessing the Explainability of Facial Skin Disease Classification Models

model-releasesarxiv-cs-cv

arXiv:2606.16794v2 Announce Type: replace Abstract: This study proposes a domain-specific LLM-based Visual Explanation Evaluation Framework for assessing visual attention explanations in facial skin d

LMEB: Long-horizon Memory Embedding Benchmark

arXiv:2603.12572v5 Announce Type: replace Abstract: Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchm

Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature

arXiv:2607.22381v1 Announce Type: new Abstract: Curvature notions on graphs, particularly Ollivier-Ricci and Forman, have emerged as powerful tools for addressing fundamental issues in Graph Neural Ne

Local Multimodal Music Alignment from Global Supervision

arXiv:2607.10023v2 Announce Type: replace-cross Abstract: Understanding music requires understanding localized relationships across data modalities, e.g., how time in performance audio maps onto posit

safetyarxiv-cs-lg

Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation

arXiv:2607.21622v1 Announce Type: cross Abstract: We prove that two canonical local synaptic learning rules, the potentiation arm of spike-timing-dependent plasticity (STDP^+) and homeostatic plastici

Longitudinal Random Forests for Sparse and Irregular Response Trajectories

arXiv:2607.21817v1 Announce Type: cross Abstract: Longitudinal studies often collect data at sparse, irregular, and unequally spaced time points. Such heterogeneity is often driven by subject-specific

Looped Latent Attention: Cross-Loop KV Compression for Looped Transformers

arXiv:2607.15456v2 Announce Type: replace-cross Abstract: Looped, weight-tied Transformers reduce parameters by reusing a single block, but decoding still stores a separate K/V cache for every recurre

safetyarxiv-cs-cl

Low-Altitude Channel Multipath Prediction via Panoramic Perception and Vision-Language Model

arXiv:2607.21953v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) communication is expected to support a wide range of low-altitude applications in 6G mobile networks. However, traditional

LunarFM: A Shared Multimodal Representation of the Moon's Surface

arXiv:2607.22408v1 Announce Type: new Abstract: The renewed global focus on lunar exploration, driven by the prospect of in-situ resource utilization and a sustained human presence on the Moon, has cr

MA-DAR: Manifold-Aligned Dynamic Adaptive Routing for Continual Temporal Knowledge Graph Reasoning

arXiv:2607.21949v1 Announce Type: new Abstract: Continual temporal knowledge graph (TKG) reasoning aims to continuously incorporate newly emerging facts while preserving previously acquired knowledge.

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Mag4D-SLAM Dataset: A Repeated-Traversal Multi-Modal 4D Geomagnetic Dataset for Localization and Mapping

arXiv:2607.21986v1 Announce Type: new Abstract: Geomagnetic sensing offers an infrastructure-free, absolute orientation reference that is robust to GNSS denial and visual degradation, yet no large-sca

researcharxiv-cs-ro

Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models

arXiv:2607.21636v1 Announce Type: new Abstract: Synthetic tabular data is valued for preserving not only each column's marginal distribution but the dependencies between columns -- structure that carr

Medical-Checklist: Assessing the Comprehension of Medical Images by Multimodal Models

model-releasesarxiv-cs-cv

arXiv:2607.21998v1 Announce Type: new Abstract: This paper introduces a new benchmark test, Medical-Checklist, for assessing medical multimodal models. The recent advancements in multimodal models hav

MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph

arXiv:2508.12393v3 Announce Type: replace Abstract: The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet curr

agentsarxiv-cs-cl

MemNMF: Memory-Augmented NMF on LPC Spectra for Anomalous Sound Detection

arXiv:2607.22086v1 Announce Type: cross Abstract: Autoencoder-based anomalous sound detection is attractive for machine condition monitoring because it can be trained using only normal recordings and

Applications

Meta-Learning Approaches for Speaker-Dependent Voice Fatigue Models

arXiv:2505.23378v3 Announce Type: replace Abstract: Speaker-dependent modelling can substantially improve performance in speech-based health monitoring applications. While mixed-effect models are comm

applicationsarxiv-cs-lg

MEUSLI: a Multilingual Projector for LLM-based ASR and Beyond

arXiv:2607.22100v1 Announce Type: new Abstract: Lightweight projectors are an established way to connect pre-trained speech encoders with large language models (LLMs), mapping acoustic features into t

researcharxiv-cs-cl

Minimum Norm Interpolation via the Local Theory of Banach Spaces: The Role of 2-Uniform Convexity

arXiv:2603.28956v2 Announce Type: replace-cross Abstract: The minimum-norm interpolator (MNI) framework has recently attracted considerable attention as a tool for understanding generalization in over

safetyarxiv-cs-lg

Local Ai

MissHyper: Restoring Clinical Synchronicity in Missingness-Guided Hypergraph Forecasting

arXiv:2607.21922v1 Announce Type: new Abstract: Clinical irregular multivariate time series are shaped not only by physiological dynamics but also by the measurement process that determines when and w

local-aiarxiv-cs-lg

MoE^2-LoRA: When MoE Models Meet MoE-style Low-Rank Adaptation

arXiv:2607.21978v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures have been widely adopted in large language models, yet parameter-efficient fine-tuning (PEFT) for MoE models rema

Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning

arXiv:2607.21653v1 Announce Type: cross Abstract: Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstrea

safetyarxiv-cs-cl

MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion

arXiv:2607.21634v1 Announce Type: new Abstract: Masked discrete diffusion for molecular graph generation typically applies a uniform corruption schedule to all tokens in a lossless graph-to-sequence r

Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token

Multi-Agent Debate and Visual Information Extraction for SeePhys Pro: A 1st-Place Technical Report from ICML 2026 AI4Math Track 3 Challenge

arXiv:2607.21946v1 Announce Type: new Abstract: This technical report presents our approach to Challenge Track~3: SeePhys Pro at the 3rd AI for Math Workshop, where the task is to answer college-level

agentsarxiv-cs-lg

Multi-Horizon Consistency as Geometry: When Latent Dynamics Contract, and When They Do Not

arXiv:2607.21645v1 Announce Type: new Abstract: Multi-horizon latent consistency is a common training knob in video predictors and world models, but practitioners rarely know what it does to transitio

Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode

arXiv:2607.22083v1 Announce Type: cross Abstract: We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-

safetyarxiv-cs-cl

Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos

arXiv:2607.21805v1 Announce Type: cross Abstract: We study the long-term behavior of the Multiplicative Weights Update (MWU) algorithm in game settings where learning dynamics frequently fail to conve

Neural Feature Governance: Extending Atom Prevalence

arXiv:2607.21671v1 Announce Type: new Abstract: Neural network compression and interpretability remain open challenges in modern deep learn- ing, where billion-parameter architectures deliver impressi

Numerical Fragility in Transformers: A Layer-wise Theory for Risk Estimation and Selective Stabilization

arXiv:2510.21770v2 Announce Type: replace Abstract: Low-precision execution can induce substantial forward discrepancies in Transformers even for fixed weights and input, yet these discrepancies are u

NWaaS: A Non-Intrusive and Privacy-Preserving Watermarking-as-a-Service System with Adaptive Resource Scheduling

model-releasesarxiv-cs-cv

arXiv:2507.18036v2 Announce Type: replace-cross Abstract: Securing intellectual property (IP) in Machine Learning as a Service is critical yet challenging. While deep neural network watermarking serve