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Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment

arXiv:2604.10627v1 Announce Type: cross Abstract: How the brain supports language across different languages is a basic question in neuroscience and a useful test for multilingual artificial intellige

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ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation

DGX agent

arXiv:2604.11386v1 Announce Type: cross Abstract: Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabli

safetyarxiv-cs-cv

14 Apr 2026

Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification

model-releasesarxiv-cs-lg

arXiv:2505.11237v3 Announce Type: replace-cross Abstract: Metaphorical imagination, the ability to connect seemingly unrelated concepts, is fundamental to human cognition and communication. While unde

ConceptPose: Training-Free Zero-Shot Object Pose Estimation using Concept Vectors

arXiv:2512.09056v3 Announce Type: replace Abstract: Object pose estimation is a fundamental task in computer vision and robotics, yet most methods require extensive, dataset-specific training. Concurr

researcharxiv-cs-cv

ConfigSpec: Profiling-Based Configuration Selection for Distributed Edge--Cloud Speculative LLM Serving

arXiv:2604.09722v1 Announce Type: cross Abstract: Speculative decoding enables collaborative Large Language Model (LLM) inference across cloud and edge by separating lightweight token drafting from he

Conflicts Make Large Reasoning Models Vulnerable to Attacks

arXiv:2604.09750v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have achieved remarkable performance across diverse domains, yet their decision-making under conflicting objectives rema

CONSCIENTIA: Can LLM Agents Learn to Strategize? Emergent Deception and Trust in a Multi-Agent NYC Simulation

arXiv:2604.09746v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed as autonomous agents, understanding how strategic behavior emerges in multi-agent environmen

Consensus-based Recursive Multi-Output Gaussian Process

arXiv:2604.10146v1 Announce Type: new Abstract: Multi-output Gaussian Processes provide principled uncertainty-aware learning of vector-valued fields but are difficult to deploy in large-scale, distri

agentsarxiv-cs-lg

Consistency of AI-Generated Exercise Prescriptions: A Repeated Generation Study Using a Large Language Model

arXiv:2604.11287v1 Announce Type: new Abstract: Background: Large language models (LLMs) have been explored as tools for generating personalized exercise prescriptions, yet the consistency of outputs

Local Ai

Consistent realism in image2 video? Comfy only, o post-processing?

local-air-stablediffusion

This r/StableDiffusion thread discusses the challenge of achieving consistent realism in AI-generated image-to-video workflows, debating whether results can be attained purely through ComfyUI-based pi

Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration

arXiv:2601.07224v2 Announce Type: replace Abstract: While Hybrid Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) has become the standard paradigm for training LLM agents, effectiv

Constrained Assumption-Based Argumentation Frameworks

arXiv:2602.13135v2 Announce Type: replace Abstract: Assumption-based Argumentation (ABA) is a well-established form of structured argumentation. ABA frameworks with an underlying atomic language are w

Content moderation is a great use case for moderation

Content moderation is a great use case for moderation new middleware integration just dropped! the langchain azure ai package now ships w/ a suite of content moderation middleware! use this for text/i

agentsharrison-chase--x

Context-Aware Semantic Segmentation via Stage-Wise Attention

model-releasesarxiv-cs-cv

arXiv:2601.11310v2 Announce Type: replace Abstract: Semantic ultra-high-resolution (UHR) image segmentation is essential in remote sensing applications such as aerial mapping and environmental monitor

Context-Guided Decompilation: A Step Towards Re-executability

arXiv:2511.01763v2 Announce Type: replace-cross Abstract: Binary decompilation plays an important role in software security analysis, reverse engineering, and malware understanding when source code is

tutorialsarxiv-cs-ai

Context Kubernetes: Declarative Orchestration of Enterprise Knowledge for Agentic AI Systems

arXiv:2604.11623v1 Announce Type: new Abstract: We introduce Context Kubernetes, an architecture for orchestrating enterprise knowledge in agentic AI systems, with a prototype implementation and eight

Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

arXiv:2604.10344v1 Announce Type: new Abstract: The classical approach to detecting depression from vision emphasizes interpretable features, such as facial expression, and classifiers such as the Sup

safetyarxiv-cs-cv

Continuous Adversarial Flow Models

arXiv:2604.11521v1 Announce Type: cross Abstract: We propose continuous adversarial flow models, a type of continuous-time flow model trained with an adversarial objective. Unlike flow matching, which

tutorialsarxiv-cs-cv

Continuous PT-Symmetry Breaking as a Design Variable for Giant Altermagnetic Spin Splitting

arXiv:2604.10173v1 Announce Type: cross Abstract: Magnetic point-group analysis classifies altermagnets but returns only a binary symmetry verdict, leaving spin-splitting energy (SSE) inaccessible wit

researcharxiv-cs-lg

Continuous-time Online Learning via Mean-Field Neural Networks: Regret Analysis in Diffusion Environments

arXiv:2604.10958v1 Announce Type: cross Abstract: We study continuous-time online learning where data are generated by a diffusion process with unknown coefficients. The learner employs a two-layer ne

Contour Refinement using Discrete Diffusion in Low Data Regime

arXiv:2602.05880v2 Announce Type: replace Abstract: Boundary detection of irregular and translucent objects is an important problem with applications in medical imaging, environmental monitoring and m

safetyarxiv-cs-cv

Controllable and Verifiable Tool-Use Data Synthesis for Agentic Reinforcement Learning

arXiv:2604.09813v1 Announce Type: new Abstract: Existing synthetic tool-use corpora are primarily designed for offline supervised fine-tuning, yet reinforcement learning (RL) requires executable envir

Controlling Multimodal Conversational Agents with Coverage-Enhanced Latent Actions

arXiv:2601.07516v2 Announce Type: replace-cross Abstract: Vision-language models are increasingly employed as multimodal conversational agents (MCAs) for diverse conversational tasks. Recently, reinfo

tutorialsarxiv-cs-ai

ConvFormer3D-TAP: Phase/Uncertainty-Aware Front-End Fusion for Cine CMR View Classification Pipelines

arXiv:2604.11389v1 Announce Type: new Abstract: Reliable recognition of standard cine cardiac MRI views is essential because each view determines which cardiac anatomy is visualized and which quantita

researcharxiv-cs-cv

Cooperation in Human and Machine Agents: Promise Theory Considerations

arXiv:2604.10505v1 Announce Type: new Abstract: Agent based systems are more common than we may think. A Promise Theory perspective on cooperation, in systems of human-machine agents, offers a unified

Copado releases Agentia, a context-aware AI agent DevOps solution for Salesforce

Copado Inc., a low-code DevOps solution provider for Salesforce, today announced the release of Agentia, an artificial intelligence solution that embeds context-aware AI agents into Salesforce. The so

agentssiliconangle

CoPS: Conditional Prompt Synthesis for Zero-Shot Anomaly Detection

arXiv:2508.03447v2 Announce Type: replace Abstract: Recently, large pre-trained vision-language models have shown remarkable performance in zero-shot anomaly detection (ZSAD). With fine-tuning on a si

safetyarxiv-cs-cv

CoRe-ECG: Advancing Self-Supervised Representation Learning for 12-Lead ECG via Contrastive and Reconstructive Synergy

arXiv:2604.11359v1 Announce Type: new Abstract: Accurate interpretation of electrocardiogram (ECG) remains challenging due to the scarcity of labeled data and the high cost of expert annotation. Self-

tutorialsarxiv-cs-ai

COREY: A Prototype Study of Entropy-Guided Operator Fusion with Hadamard Reparameterization for Selective State Space Models

arXiv:2604.10597v1 Announce Type: cross Abstract: State Space Models (SSMs), represented by the Mamba family, provide linear-time sequence modeling and are attractive for long-context inference. Yet p

Local Ai

Correct me if I’m wrong: Ollama can’t fine tune like Unsloth Studio

Ollama is a local inference engine designed for running pre-built LLMs on your own machine, and it does not include fine-tuning capabilities — this distinction is correct. Unsloth (and its Unsloth Stu

local-air-ollama

COSMIK-MPPI: Scaling Constrained Model Predictive Control to Collision Avoidance in Close-Proximity Dynamic Human Environments

arXiv:2604.10358v1 Announce Type: new Abstract: Ensuring safe physical interaction between torque-controlled manipulators and humans is essential for deploying robots in everyday environments. Model P

safetyarxiv-cs-ro

Cost-optimal Sequential Testing via Doubly Robust Q-learning

arXiv:2604.11165v1 Announce Type: cross Abstract: Clinical decision-making often involves selecting tests that are costly, invasive, or time-consuming, motivating individualized, sequential strategies

CoSToM:Causal-oriented Steering for Intrinsic Theory-of-Mind Alignment in Large Language Models

arXiv:2604.10031v1 Announce Type: cross Abstract: Theory of Mind (ToM), the ability to attribute mental states to others, is a hallmark of social intelligence. While large language models (LLMs) demon

CounterBench: Evaluating and Improving Counterfactual Reasoning in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2502.11008v2 Announce Type: replace Abstract: Counterfactual reasoning is widely recognized as one of the most challenging and intricate aspects of causality in artificial intelligence. In this

Counting to Four is still a Chore for VLMs

model-releasesarxiv-cs-cv

arXiv:2604.10039v1 Announce Type: new Abstract: Vision--language models (VLMs) have achieved impressive performance on complex multimodal reasoning tasks, yet they still fail on simple grounding skill

CountLoop: Training-Free High-Instance Image Generation via Iterative Agent Guidance

arXiv:2508.16644v4 Announce Type: replace Abstract: Diffusion models excel at photorealistic synthesis but struggle with precise object counts, especially in high-density settings. We introduce COUNTL

agentsarxiv-cs-cv

COXNet: Cross-Layer Fusion with Adaptive Alignment and Scale Integration for RGBT Tiny Object Detection

arXiv:2508.09533v2 Announce Type: replace-cross Abstract: Detecting tiny objects in multimodal Red-Green-Blue-Thermal (RGBT) imagery is a critical challenge in computer vision, particularly in surveil

CPAM: Context-Preserving Adaptive Manipulation for Zero-Shot Real Image Editing

model-releasesarxiv-cs-cv

arXiv:2506.18438v2 Announce Type: replace Abstract: Editing natural images using textual descriptions in text-to-image diffusion models remains a significant challenge, particularly in achieving consi

Applications

CraftGraffiti: Exploring Human Identity with Custom Graffiti Art via Facial-Preserving Diffusion Models

arXiv:2508.20640v2 Announce Type: replace Abstract: Preserving facial identity under extreme stylistic transformation remains a major challenge in generative art. In graffiti, a high-contrast, abstrac

applicationsarxiv-cs-cv

Creative Direct with Hermes

Nous Research shared a post on X (formerly Twitter) discussing 'Creative Direct with Hermes,' likely showcasing the creative writing or instruction-following capabilities of their Hermes language mode

agentsnous-research--x

Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision

arXiv:2604.10182v1 Announce Type: new Abstract: Current evaluations of autonomous coding agents assume an unrealistic, infinite-resource environment. However, real-world software engineering is a reso

Hardware

Credo to acquire Israeli silicon photonics startup DustPhotonics for up to $1.3 billion

Fabless chip design company Credo Technology Group Holding Ltd. today announced that it has reached a deal to acquire Israeli silicon photonics startup DustPhotonics Ltd. for up to 1.3 billion in cash

hardwaresiliconangle

CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics

arXiv:2512.21877v3 Announce Type: replace-cross Abstract: Cricket is the second most popular sport worldwide, with billions of fans seeking advanced statistical insights unavailable through standard w

Critical-CoT: A Robust Defense Framework against Reasoning-Level Backdoor Attacks in Large Language Models

arXiv:2604.10681v1 Announce Type: cross Abstract: Large Language Models (LLMs), despite their impressive capabilities across domains, have been shown to be vulnerable to backdoor attacks. Prior backdo

CROP: Conservative Reward for Model-based Offline Policy Optimization

arXiv:2310.17245v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) aims to optimize a policy using collected data without online interactions. Model-based approaches are par

Cross-Cultural Bias in Mel-Scale Representations: Evidence and Alternatives from Speech and Music

arXiv:2604.10503v1 Announce Type: cross Abstract: Modern audio systems universally employ mel-scale representations derived from 1940s Western psychoacoustic studies, potentially encoding cultural bia

Cross-Cultural Value Awareness in Large Vision-Language Models

arXiv:2604.09945v1 Announce Type: cross Abstract: The rapid adoption of large vision-language models (LVLMs) in recent years has been accompanied by growing fairness concerns due to their propensity t

Cross-Validated Cross-Channel Self-Attention and Denoising for Automatic Modulation Classification

model-releasesarxiv-cs-lg

arXiv:2604.10054v1 Announce Type: new Abstract: This study addresses a key limitation in deep learning Automatic Modulation Classification (AMC) models, which perform well at high signal-to-noise rati