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Context-aware child-directed speech detection from long-form recordings

arXiv:2606.01134v1 Announce Type: cross Abstract: Automatically distinguishing child-directed speech from adult-directed speech in long-form recordings is key to scalable analyses of children's langua

researcharxiv-cs-lg

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Human DGX agent

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Context Matters: Repository-Aware Security Analysis of the Agent Skill Ecosystem

DGX agent

arXiv:2603.16572v2 Announce Type: replace-cross Abstract: Agent skills extend local AI agents, such as Claude Code and OpenClaw, with additional functionality. Their growing popularity has led to dedi

model-releasesarxiv-cs-ai

2 Jun 2026

Continual Learning as a Multiphase Moving-Boundary Problem

arXiv:2606.01863v1 Announce Type: new Abstract: Continual learning struggles to balance retaining past knowledge with absorbing new tasks. Stefan-CL elegantly resolves this stability-plasticity dilemm

researcharxiv-cs-lg

Continuous Reasoning for Vision-Language-Action

arXiv:2606.00229v1 Announce Type: cross Abstract: Natural language is a powerful reasoning medium for language and vision-language models, but it is mismatched to the granularity of continuous control

researcharxiv-cs-ai

ContinuousBench: Can Differentially Private Synthetic Text Improve Capabilities?

arXiv:2606.01849v1 Announce Type: cross Abstract: Differentially private (DP) text synthesis promises to unlock sensitive corpora for model training, but it remains unclear whether DP synthetic data t

Applications

Contrastive Augmented Transformer with Domain-specific Enhancement for Robust Multi-scenario Metal Surface Defect Detection

arXiv:2606.01962v1 Announce Type: new Abstract: Metal surface defect detection is critical for maintaining product quality in industrial manufacturing. However, it faces significant challenges, includ

applicationsarxiv-cs-cv

Contrastive meta-domain adaptation for robust skin lesion classification across clinical and acquisition conditions

arXiv:2602.19857v2 Announce Type: replace Abstract: Deep learning models for dermatological image analysis remain sensitive to acquisition variability and domain-specific visual characteristics, leadi

Control of a Twin Rotor using Twin Delayed Deep Deterministic Policy Gradient (TD3)

arXiv:2512.13356v2 Announce Type: replace-cross Abstract: This paper proposes a reinforcement learning (RL) framework for controlling and stabilizing the Twin Rotor Aerodynamic System (TRAS) at specif

Controllable Value Alignment in Large Language Models through Neuron-Level Editing

model-releasesarxiv-cs-lg

arXiv:2602.07356v2 Announce Type: replace Abstract: Aligning large language models (LLMs) with human values has become increasingly important as their influence on human behavior and decision-making e

Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation

arXiv:2606.02047v1 Announce Type: cross Abstract: We introduce Convex Distance Operator Transport (CDOT), the first convex optimal transport framework that aligns distributions across heterogeneous do

researcharxiv-cs-lg

Applications

Cooperation of Experts: Fusing Heterogeneous Information with Large Margin

arXiv:2505.20853v3 Announce Type: replace-cross Abstract: Fusing heterogeneous information remains a persistent challenge in modern data analysis. While significant progress has been made, existing ap

applicationsarxiv-cs-ai

Coordinating Task Switching in a Robotics Multi-Agent System Using Behavior Trees

arXiv:2606.01170v1 Announce Type: cross Abstract: The application of multi-agent systems in robotics is a very challenging field. Several competitions involving such systems are proposed to foster res

agentsarxiv-cs-ro

Coordination Graphs for Constrained Multi-Agent Reinforcement Learning

arXiv:2606.02337v1 Announce Type: new Abstract: Constrained Multi-agent reinforcement learning (CMARL) faces two intertwined challenges: the joint action space grows exponentially with the number of a

agentsarxiv-cs-ai

COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs

arXiv:2606.00700v1 Announce Type: cross Abstract: Online link recommendation on evolving graphs is performative: by choosing which candidate links to show users, the system changes which links form an

CORE-MTL: Rethinking Gradient Balancing via Causal Orthogonal Representations

arXiv:2606.02221v1 Announce Type: new Abstract: Multi-task learning (MTL) aims to construct a joint model for multiple tasks by sharing a common representation across domains. To achieve this goal, ex

Correcting Gradient-Based Circuit Localization via Interaction-Aware Backpropagation

arXiv:2505.17630v4 Announce Type: replace Abstract: Circuit localization methods aim to identify the subset of model components responsible for specific behaviors in large language models, enabling de

Tutorials

Cortex and subcortex play distinct roles over learning when cortical memory is limited

arXiv:2606.00667v1 Announce Type: cross Abstract: It has been proposed that the brain integrates flexible, computationally expensive cortical processing with simpler, lower-cost subcortical mechanisms

tutorialsarxiv-cs-lg

Cost-Aware Diffusion Draft Trees for Speculative Decoding

arXiv:2606.01813v1 Announce Type: new Abstract: Speculative decoding accelerates inference by having a lightweight drafter propose tokens verified in parallel by the target language model. Block diffu

researcharxiv-cs-cl

Local Ai

CoSTL: Comprehensive Spatial-Temporal Representation Learning for Moment Retrieval and Highlight Detection

arXiv:2606.01149v1 Announce Type: new Abstract: Video Moment Retrieval (MR) and Highlight Detection (HD) are crucial tasks in video analysis that aim to localize specific moments and estimate clip-wis

local-aiarxiv-cs-cv

Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification

arXiv:2208.00967v4 Announce Type: replace Abstract: Graph-based models have achieved great success in person re-identification tasks recently, which compute the graph topology structure (affinities) a

CountGD++: Generalized Prompting for Open-World Counting

arXiv:2512.23351v2 Announce Type: replace Abstract: The flexibility and accuracy of methods for automatically counting objects in images and videos are limited by the way the object can be specified.

agentsarxiv-cs-cv

Applications

Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials

arXiv:2606.00315v1 Announce Type: new Abstract: Modern generative machine learning (ML) models can propose novel inorganic crystalline materials with targeted properties; however, synthesis planning o

applicationsarxiv-cs-ai

CR-JEPA: Cross-Modal Joint-Embedding Predictive Learning for Remote Sensing Image Retrieval

arXiv:2606.00706v1 Announce Type: new Abstract: Cross-modal remote sensing image retrieval aims to retrieve semantically related scenes across heterogeneous sensing modalities. This remains challengin

safetyarxiv-cs-cv

CRAB-Bench: Evaluating LLM Agents under Complex Task Dependencies and Human-aligned User Simulation

arXiv:2606.01815v1 Announce Type: new Abstract: Evaluating LLM agents in realistic service scenarios requires complex task dependencies, imperfect user behavior, and an evaluation that accommodates mu

Hardware

CRAFT: Fine-Grained Cost-Aware Expert Replication For Efficient Mixture-of-Experts Serving

arXiv:2603.28768v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has recently emerged as the mainstream architecture for efficiently scaling large language models while maintaining n

hardwarearxiv-cs-lg

Tutorials

CRAFTQA: A Code-Driven Adaptive Framework for Complex Structured Data Reasoning

arXiv:2606.02170v1 Announce Type: new Abstract: Real-world scenarios involve massive heterogeneous structured data (e.g., tables, knowledge graphs), making effective reasoning over such diverse data i

tutorialsarxiv-cs-cl

CRAM: Centroid-Routing and Adaptive MoE for Multimodal Continual Instruction Tuning

arXiv:2606.02502v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) unify heterogeneous vision-language tasks under a shared generative framework via instruction tuning, yet real-

Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX

arXiv:2606.01478v1 Announce Type: cross Abstract: High-quality, large-scale synthetic data from simulations is becoming a cornerstone for pushing the capabilities of robot algorithms. While aerial rob

CrazyMARL: Decentralized Direct Motor Control Policies for Cooperative Aerial Transport of Cable-Suspended Payloads

arXiv:2509.14126v2 Announce Type: replace Abstract: Collaborative transportation of cable-suspended payloads by teams of UAVs has the potential to enhance payload capacity, adapt to different payload

agentsarxiv-cs-ro

Local Ai

CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search

arXiv:2606.01544v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in practice incurs substantial memory and computational costs. Post-training pruning (PTP) is an effective approa

local-aiarxiv-cs-lg

Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback

arXiv:2606.00590v1 Announce Type: cross Abstract: Agentic search systems iteratively interact with retrieval models to answer complex queries. Despite substantial progress, optimizing retrievers for a

agentsarxiv-cs-ai

CRMA: A Spectrally-Bounded Backbone for Modular Continual Fine-Tuning of LLMs

model-releasesarxiv-cs-lg

arXiv:2606.00382v1 Announce Type: new Abstract: Sequential fine-tuning of large language models forces a choice: let the shared substrate keep learning and accept catastrophic forgetting, or freeze it

Cross-Axis Feature Fusion with Joint-Wise Motion Difference Prediction for Text-Based 3D Human Motion Editing

arXiv:2606.01014v1 Announce Type: cross Abstract: We address text-based 3D human motion editing, where the goal is to preserve the style and structure of a source motion while applying edits described

Cross-Domain Dead Tree Detection via Knowledge Distillation in Aerial Imagery

arXiv:2606.02303v1 Announce Type: new Abstract: Detecting dead trees in aerial imagery is vital for assessing forest health, especially as tree mortality increases globally due to climate change, but

safetyarxiv-cs-cv

Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation

arXiv:2602.05217v2 Announce Type: replace Abstract: Cross-Domain Few-Shot Segmentation aims to segment categories in data-scarce domains conditioned on a few exemplars. Typical methods first establish

Cross-Environment Neural Reranking for Sample-Efficient Action Selection in Text-Based Agents

arXiv:2606.02204v1 Announce Type: new Abstract: Large language model agents achieve strong performance on text-based benchmarks but incur prohibitive inference costs, motivating the use of compact neu

Cross-Generational Transfer of Adversarial Attacks Reveals Non-Monotonic Safety Alignment in LLMs

arXiv:2606.00813v1 Announce Type: cross Abstract: Safety alignment in LLMs does not improve monotonically across model generations. Studying four generations of Google's Gemma family (7B-31B) with qua

Cross-lingual Self-Consistency for Multilingual Reasoning with Language Models

arXiv:2606.01464v1 Announce Type: new Abstract: Despite expanding their multilingual coverage, the advanced reasoning capabilities of LLMs remain largely confined to a few high-resource languages like

researcharxiv-cs-cl

Cross-modal linkage risk in clinical vision-language models

arXiv:2606.02276v1 Announce Type: cross Abstract: Vision-language models (VLMs) trained on paired chest radiographs and radiology reports learn a shared embedding space that can preserve instance-leve

Local Ai

CryoProt: A Protein Pretraining Framework with Cross-Box Interactions on Cryo-EM Density Maps

arXiv:2606.00955v1 Announce Type: new Abstract: Despite the growing availability of cryo-electron microscopy (cryo-EM) density maps, effectively leveraging them for protein representation remains chal

local-aiarxiv-cs-lg

CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards

model-releasesarxiv-cs-ai

arXiv:2606.00020v1 Announce Type: cross Abstract: Large Language Model (LLM) based Chinese Grammatical Error Correction (CGEC) systems face two critical challenges: general-purpose models lack special

CultureForest: Understanding and Evaluating Cultural Norm Grounded Reasoning in LLMs

arXiv:2606.01879v1 Announce Type: new Abstract: Existing research largely reduces cultural intelligence in LLMs to a knowledge-level problem, overlooking whether models can effectively utilize their a

CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM

arXiv:2606.00846v1 Announce Type: new Abstract: Users increasingly face the challenge of selecting an appropriate LLM for a given task from a rapidly growing pool of LLMs, each with distinct but often

safetyarxiv-cs-lg

CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs

arXiv:2602.00742v2 Announce Type: replace Abstract: User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Larg

researcharxiv-cs-cl

Cuttlebot: a platform demonstration for complex, autonomous, bio-inspired swimmers

arXiv:2606.00197v1 Announce Type: new Abstract: Increasing interest in deep-sea operations and resources motivates the development of ecologically sensitive but environmentally durable robots. Dielect

agentsarxiv-cs-ro

CV-Arena: An Open Benchmark for Instructional Computer Vision Problem Solving with Human-AI Collaborative Preferences

model-releasesarxiv-cs-ai

arXiv:2606.00931v1 Announce Type: cross Abstract: Instruction-guided image editing is becoming a general interface for visual work, yet existing benchmarks still focus largely on narrow appearance edi

d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation

arXiv:2509.21474v4 Announce Type: replace Abstract: While diffusion language models (DLMs) have achieved competitive performance in text generation, improving their reasoning ability with reinforcemen

safetyarxiv-cs-lg

DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts

model-releasesarxiv-cs-ai

arXiv:2606.01062v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have become a leading approach for decoupling parameter count from computational cost in large language models, yet effe