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Latent-Mark: An Audio Watermark Robust to Neural Codec Compression

arXiv:2603.05310v3 Announce Type: replace-cross Abstract: While existing audio watermarking techniques have achieved strong robustness against traditional digital signal processing (DSP) attacks, they

researcharxiv-cs-ai

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Layer-Specific Prompt Fusion Discovery via Differentiable Search in Vision Foundation Models

DGX agent

arXiv:2606.26379v1 Announce Type: new Abstract: Visual prompt tuning has emerged as a parameter-efficient fine-tuning approach for adapting large-scale Vision Transformers (ViTs) to downstream tasks.

model-releasesarxiv-cs-cv

26 Jun 2026

Layered Outer-Loop Control for Disturbance-Robust Multi-Waypoint UAV Arrival

model-releasesarxiv-cs-ro

arXiv:2606.26315v1 Announce Type: new Abstract: Disturbance-robust UAV position control is easy to demonstrate in benign simulations but much harder to make fast in approach, well behaved near the tar

LayersReg: A Layer-by-Layer Progressive Regressor for Reliable Intraoperative 3D/2D Registration

arXiv:2606.26647v1 Announce Type: new Abstract: 3D/2D registration serves as a cornerstone technique in surgical navigation. Traditional iterative optimization algorithms suffer from low efficiency an

safetyarxiv-cs-cv

LCAi: Life Cycle Assessment with big data fusion and retrieval-augmented generation-assisted interpretation

arXiv:2606.26857v1 Announce Type: new Abstract: The interpretation phase of life cycle assessment often lacks structured mechanisms for translating quantified improvement opportunities addressing envi

LCG: Long-Context Consistent Image Generation with Sparse Relational Attention

arXiv:2606.26171v1 Announce Type: cross Abstract: Recent image generation models achieve impressive quality in single-image synthesis, but often fail to maintain consistency across sequential outputs,

safetyarxiv-cs-ai

LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration

arXiv:2606.26778v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have driven substantial progress in image and video generation but suffer from prohibitive computational costs. Feature ca

researcharxiv-cs-cv

Local Ai

Learning Adversarial Augmentation Policies for Robust Garlic Seedling Detection

arXiv:2606.26828v1 Announce Type: new Abstract: Accurate seedling detection during early growth stages is essential for timely replanting and effective crop management in precision agriculture. Howeve

local-aiarxiv-cs-cv

Learning from a Biased Sample

arXiv:2209.01754v5 Announce Type: replace-cross Abstract: The empirical risk minimization approach to data-driven decision making requires access to training data drawn under the same conditions as th

Learning from Equivalence Queries, Revisited

arXiv:2604.04535v2 Announce Type: replace Abstract: Modern machine learning systems, such as generative models and recommendation systems, often evolve through a cycle of deployment, user interaction,

researcharxiv-cs-lg

Learning from the Self-future: On-policy Self-distillation for dLLMs

arXiv:2606.18195v2 Announce Type: replace Abstract: On-policy self-distillation (OPSD) has proven effective for post-training large language models (LLMs), yet its application to diffusion LLMs (dLLMs

safetyarxiv-cs-cl

Learning Language-Driven Sequence-Level Modal-Invariant Representations for Video-Based Visible-Infrared Person Re-Identification

arXiv:2601.12062v2 Announce Type: replace Abstract: The core of video-based visible-infrared person re-identification (VVI-ReID) lies in learning sequence-level modal-invariant representations across

Learning Long-Range Dependencies with Temporal Predictive Coding

model-releasesarxiv-cs-lg

arXiv:2602.18131v2 Announce Type: replace Abstract: Temporal Predictive Coding provides a layer-local, parallelisable mechanism for learning in recurrent systems, making it an attractive candidate for

Learning Motion Feasibility from Point Clouds in Cluttered Environments

arXiv:2606.26700v1 Announce Type: cross Abstract: Motion feasibility prediction plays a central role in robotics, particularly in task and motion planning and manipulation. A major bottleneck for this

Learning Probabilistic Filters with Strictly Proper Scoring Rules

arXiv:2606.26497v1 Announce Type: new Abstract: Bayesian filtering of partially and noisily observed dynamical systems seeks to infer the evolving conditional distribution of the state of a dynamical

Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation

arXiv:2509.20008v2 Announce Type: replace Abstract: Penetration testing, the simulation of cyberattacks to identify security vulnerabilities, presents a sequential decision-making problem well-suited

Agents

Learning to Explain Air Traffic Situation

arXiv:2502.10764v4 Announce Type: replace Abstract: Understanding how air traffic controllers construct a mental 'picture' of complex air traffic situations is crucial but remains a challenge due to t

agentsarxiv-cs-lg

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline)

arXiv:2606.27163v1 Announce Type: cross Abstract: I describe my solution to the LeHome Challenge 2026, an ICRA 2026 competition on bimanual garment folding. The system placed 1st of 62 teams in the on

safetyarxiv-cs-ai

Learning to Recover Task Experts from a Multi-Task Merged Model

arXiv:2606.26902v1 Announce Type: new Abstract: Multi-task model merging aims to consolidate several task-specific experts into a unified model, yet static merging consistently suffers from parameter

Learning to Select Maximum Clique Algorithms: From Traditional Machine Learning to a Dual-Channel Hybrid Neural Architecture

arXiv:2508.08005v4 Announce Type: replace-cross Abstract: The Maximum Clique Problem (MCP) is an NP-hard problem with wide-ranging applications in fields such as bioinformatics, network science, and s

Agents

Learning User Simulators with Turing Rewards

arXiv:2606.19336v2 Announce Type: replace Abstract: Learning to simulate human users in interactive settings could advance the training of agent assistants, evaluation of personalization systems, rese

agentsarxiv-cs-cl

Letter: the US lifts its block on Mythos 5, allowing Anthropic to release it to more than 100 US institutions; sources: talks about Fable 5 are ongoing (Semafor)

Semafor: Letter: the US lifts its block on Mythos 5, allowing Anthropic to release it to more than 100 US institutions; sources: talks about Fable 5 are ongoing — THE SCOOP — The US government Friday

model-releasestechmeme

Life After Benchmark Saturation: A Case Study of CORE-Bench

arXiv:2606.26158v1 Announce Type: new Abstract: When a benchmark's accuracy saturates, it is often retired and replaced with a more challenging version. We show that this approach privileges accuracy

Limited Reference, Reliable Generation: A Two-Component Framework for Tabular Data Generation in Low-Data Regimes

arXiv:2509.09960v2 Announce Type: replace-cross Abstract: Synthetic tabular data generation is increasingly essential in machine learning, supporting downstream applications when real-world, high-qual

LiMoDE: Rethinking Lifelong Robot Manipulation from a Mixture-of-Dynamic-Experts Perspective

arXiv:2606.26183v1 Announce Type: cross Abstract: Building a generalist robot that can leverage prior knowledge for continuous task adaptation remains a significant challenge. Previous works alleviate

Linguistics and Human Brain: A Perspective of Computational Neuroscience

arXiv:2602.08275v3 Announce Type: replace-cross Abstract: Elucidating the language-brain relationship requires bridging the methodological gap between the abstract theoretical frameworks of linguistic

safetyarxiv-cs-cl

Liquid Fusion of Heterogeneous Representations Towards General Salient Object Detection

arXiv:2606.26849v1 Announce Type: new Abstract: General Salient Object Detection (SOD) aims to identify and segment visually interesting objects from uni-modality or multi-modality scenes, recently ad

LISA: Likelihood Score Alignment for Visual-condition Controllable Generation

arXiv:2606.27192v1 Announce Type: new Abstract: The prevalent dual-branch paradigm, i.e., training a side network to encode visual conditions and fusing its intermediate-layer features to a frozen pre

safetyarxiv-cs-cv

Listening Like a Judge: A Music-Aware Framework for Automatic Singing Performance Evaluation

arXiv:2606.26451v1 Announce Type: cross Abstract: Automatic singing quality assessment (SQA) requires evaluating lyrical correctness and musical fidelity while handling expressive variations. However,

LithoDreamer: A Physics-Informed World Model for Multi-Stage Computational Lithography

arXiv:2606.26713v1 Announce Type: new Abstract: As semiconductor technology nodes scale, computational lithography is essential for ensuring yield and performance. However, lithography is a continuous

researcharxiv-cs-ai

LiveEdit: Towards Real-Time Diffusion-Based Streaming Video Editing

arXiv:2606.26740v1 Announce Type: new Abstract: Streaming video editing has made rapid progress, yet practical deployment is still limited by two core issues: maintaining stable backgrounds and non-ed

LLM-Based Examination of Eligibility Criteria from Securities Prospectuses at the German Central Bank

arXiv:2606.27316v1 Announce Type: new Abstract: Verifying the eligibility of securities as collateral is a key responsibility of the German Central Bank. However, manually verifying these assets again

applicationsarxiv-cs-cl

LLM-based Models for Detecting Emerging Topics in Service Feedback

arXiv:2606.26595v1 Announce Type: new Abstract: Enhancing the analysis of service feedback is essential for public sector organizations, particularly tax administrations, where trust and compliance de

safetyarxiv-cs-ai

LMs as Task-Specific Knowledge Bases: An Interpretability Analysis

model-releasesarxiv-cs-cl

arXiv:2606.27237v1 Announce Type: new Abstract: Language models (LMs) capture large amounts of factual knowledge applicable to a wide range of tasks, motivating the view of their parameters as a knowl

Agents

Localizing RL-Induced Tool Use to a Single Crosscoder Feature

arXiv:2606.26474v1 Announce Type: cross Abstract: Fine-tuning through RL reshapes the internal representations of language models to enable agentic behaviors such as tool use, yet the mechanistic basi

agentsarxiv-cs-ai

LogicIR: Logic Gate Networks for Image Restoration

arXiv:2606.26609v1 Announce Type: new Abstract: Image restoration aims to reconstruct high-quality images from degraded low-quality inputs. As the computational demands of image restoration models con

researcharxiv-cs-cv

Look-Before-Move: Narrative-Grounded World Visual Attention in Dynamic 3D Story Worlds

arXiv:2606.26964v1 Announce Type: new Abstract: As embodied AI and world models increasingly operate in dynamic 3D environments, visual perception must move beyond passively interpreting given observa

Low Resource Multimodal Translation of Nepali Spoken Words into Emotion-Conditioned Sign Language Avatars

arXiv:2606.26107v1 Announce Type: cross Abstract: Sign language communication systems, that integrate emotional expression remain underexplored, particularly for low-resource languages. This pilot stu

Many companies could build their own Workday or whatever, too, using open source alternatives. They don't do that for a wide variety of reas…

applicationsethan-mollick--x

Many companies could build their own Workday or whatever, too, using open source alternatives. They don't do that for a wide variety of reasons. Same dynamics apply in AI, only more so (upgrade cycles

Mapping Political-Elite Networks in Europe with a Multilingual Joint Entity-Relation Extraction Pipeline

arXiv:2606.27347v1 Announce Type: new Abstract: Whether political elites organise into rent-seeking coalitions that capture public resources or civic networks that sustain governance is a central ques

applicationsarxiv-cs-cl

Mask to Concept: Auto-Promptable SAM3 via Efficient Test-Time Concept Embedding Search for Few-Shot Annotation

arXiv:2606.26711v1 Announce Type: new Abstract: Transforming foundation segmentation models from human-prompted tools into auto-promptable annotators is critical for scalable medical data annotation.

MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction

arXiv:2604.01958v2 Announce Type: replace Abstract: Infrared and visible video fusion combines the object saliency from infrared images with the texture details from visible images to produce semantic

researcharxiv-cs-cv

Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data

model-releasesarxiv-cs-lg

arXiv:2606.26498v1 Announce Type: cross Abstract: This paper addresses model-free continuous-time mean-field control in a setting where the population dynamics evolve continuously according to an unkn

MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models

arXiv:2603.11625v2 Announce Type: replace-cross Abstract: While specialized Medical Vision-Language Models (VLMs) have achieved remarkable success in interpreting 2D and 3D medical modalities, their d

researcharxiv-cs-ai

Meet Chauntyll Allen, a school board member at @SPPS_News. She wants to turn White Christian cemeteries into dog parks so dogs can p*** on W…

Meet Chauntyll Allen, a school board member at @SPPS_News. She wants to turn White Christian cemeteries into dog parks so dogs can p*** on White corpses. These are the people in charge of your kids’ e

applicationselon-musk--x

Memory Depth, Not Memory Access: Selective Parametric Consolidation for Long-Running Language Agents

arXiv:2606.26806v1 Announce Type: new Abstract: Long-running language agents need more than memory access. Retrieval systems can fetch past facts at query time, but they do not decide which experience

Local Ai

Mesh-RL: Coupled subgrid reinforcement learning

arXiv:2606.26333v1 Announce Type: new Abstract: Reinforcement learning in large or sparse-reward environments suffers from slow temporal-difference reward propagation, as value information spreads onl

local-aiarxiv-cs-lg

MetaboNet-Bench: A Multi-modal Benchmark for Glucose Forecasting in Type 1 Diabetes

model-releasesarxiv-cs-lg

arXiv:2606.18640v2 Announce Type: replace Abstract: Glucose forecasting algorithms are an important aspect of glycemic control management in type 1 diabetes. So far, the research community has develop