All entries

ClimateCause: Complex and Implicit Causal Structures in Climate Reports

arXiv:2604.14856v1 Announce Type: new Abstract: Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, di

CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization

DGX agent

arXiv:2604.14587v1 Announce Type: new Abstract: Lion optimizer is a popular learning-based optimization algorithm in machine learning, which shows impressive performance in training many deep learning

model-releasesarxiv-cs-lg

17 Apr 2026

Tutorials

Cloning is as Hard as Learning for Stabilizer States

arXiv:2604.15269v1 Announce Type: cross Abstract: The impossibility of simultaneously cloning non-orthogonal states lies at the foundations of quantum theory. Even when allowing for approximation erro

tutorialsarxiv-cs-lg

CMTM: Cross-Modal Token Modulation for Unsupervised Video Object Segmentation

arXiv:2604.14630v1 Announce Type: new Abstract: Recent advances in unsupervised video object segmentation have highlighted the potential of two-stream architectures that integrate appearance and motio

researcharxiv-cs-cv

Co-distilled attention guided masked image modeling with noisy teacher for self-supervised learning on medical images

arXiv:2604.14506v1 Announce Type: new Abstract: Masked image modeling (MIM) is a highly effective self-supervised learning (SSL) approach to extract useful feature representations from unannotated dat

researcharxiv-cs-cv

CobwebTM: Probabilistic Concept Formation for Lifelong and Hierarchical Topic Modeling

arXiv:2604.14489v1 Announce Type: new Abstract: Topic modeling seeks to uncover latent semantic structure in text corpora with minimal supervision. Neural approaches achieve strong performance but req

Cognitive Alpha Mining via LLM-Driven Code-Based Evolution

arXiv:2511.18850v2 Announce Type: replace Abstract: Discovering effective predictive signals, or 'alphas,' from financial data with high dimensionality and extremely low signal-to-noise ratio remains

Cognitive Offloading in Agile Teams: How Artificial Intelligence Reshapes Risk Assessment and Planning Quality

arXiv:2604.13814v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) have shown promise in automating key aspects of Agile project management, yet their impact on team cog

researcharxiv-cs-ai

Applications

Combining Bayesian and Frequentist Inference for Laboratory-Specific Performance Guarantees in Copy Number Variation Detection

arXiv:2604.14305v1 Announce Type: cross Abstract: Targeted amplicon panels are widely used in oncology diagnostics, but providing per-gene performance guarantees for copy number variant (CNV) detectio

applicationsarxiv-cs-lg

Comparison of Modern Multilingual Text Embedding Techniques for Hate Speech Detection Task

arXiv:2604.14907v1 Announce Type: new Abstract: Online hate speech and abusive language pose a growing challenge for content moderation, especially in multilingual settings and for low-resource langua

Comparison of window shapes and lengths in short-time feature extraction for classification of heart sound signals

arXiv:2604.13567v1 Announce Type: cross Abstract: Heart sound signals, phonocardiography (PCG) signals, allow for the automatic diagnosis of potential cardiovascular pathology. Such classification tas

researcharxiv-cs-ai

Compressed-Sensing-Guided, Inference-Aware Structured Reduction for Large Language Models

arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha

Compressing Sequences in the Latent Embedding Space: K-Token Merging for Large Language Models

arXiv:2604.15153v1 Announce Type: new Abstract: Large Language Models (LLMs) incur significant computational and memory costs when processing long prompts, as full self-attention scales quadratically

ConfLayers: Adaptive Confidence-based Layer Skipping for Self-Speculative Decoding

arXiv:2604.14612v1 Announce Type: cross Abstract: Self-speculative decoding is an inference technique for large language models designed to speed up generation without sacrificing output quality. It c

Conformal Policy Control

arXiv:2603.02196v2 Announce Type: replace-cross Abstract: An agent must try new behaviors to explore and improve. In high-stakes environments, an agent that violates safety constraints may cause harm

safetyarxiv-cs-lg

connect, ingest, extract, enrich

This post likely discusses a four-step framework for data processing and AI workflows: connecting to data sources, ingesting raw data, extracting relevant information, and enriching it with additional

agentsyohei-nakajima--x

Constrained Decoding for Safe Robot Navigation Foundation Models

model-releasesarxiv-cs-lg

arXiv:2509.01728v4 Announce Type: replace-cross Abstract: Recent advances in the development of robotic foundation models have led to promising end-to-end and general-purpose capabilities in robotic s

Constraint-based Pre-training: From Structured Constraints to Scalable Model Initialization

arXiv:2604.14769v1 Announce Type: new Abstract: The pre-training and fine-tuning paradigm has become the dominant approach for model adaptation. However, conventional pre-training typically yields mod

researcharxiv-cs-lg

Context Over Content: Exposing Evaluation Faking in Automated Judges

arXiv:2604.15224v1 Announce Type: cross Abstract: The extit{LLM-as-a-judge} paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: th

Contextuality from Single-State Ontological Models: An Information-Theoretic Obstruction

arXiv:2602.16716v3 Announce Type: replace Abstract: Contextuality is a central feature of quantum theory, traditionally understood as the impossibility of reproducing quantum measurement statistics us

researcharxiv-cs-ai

Applications

Continual Learning for fMRI-Based Brain Disorder Diagnosis via Functional Connectivity Matrices Generative Replay

arXiv:2604.14259v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) is widely used for studying and diagnosing brain disorders, with functional connectivity (FC) matrices pr

applicationsarxiv-cs-lg

Continuous-time reinforcement learning: ellipticity enables model-free value function approximation

arXiv:2602.06930v2 Announce Type: replace Abstract: We study off-policy reinforcement learning for controlling continuous-time Markov diffusion processes with discrete-time observations and actions. W

safetyarxiv-cs-lg

Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm

model-releasesarxiv-cs-ai

arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed 'Vibe Coding') exposes a critical Context-Fidelity Trade-off: vague user intents ove

ContractSkill: Repairable Contract-Based Skills for Multimodal Web Agents

model-releasesarxiv-cs-ai

arXiv:2603.20340v3 Announce Type: replace-cross Abstract: Self-generated skills for web agents are often unstable and can even hurt performance relative to direct acting. We argue that the key bottlen

ControlFoley: Unified and Controllable Video-to-Audio Generation with Cross-Modal Conflict Handling

model-releasesarxiv-cs-cv

arXiv:2604.15086v1 Announce Type: cross Abstract: Recent advances in video-to-audio (V2A) generation enable high-quality audio synthesis from visual content, yet achieving robust and fine-grained cont

Controllable Video Object Insertion via Multiview Priors

arXiv:2604.14556v1 Announce Type: new Abstract: Video object insertion is a critical task for dynamically inserting new objects into existing environments. Previous video generation methods focus prim

safetyarxiv-cs-cv

Controlling Authority Retrieval: A Missing Retrieval Objective for Authority-Governed Knowledge

arXiv:2604.14488v1 Announce Type: cross Abstract: In any domain where knowledge accumulates under formal authority -- law, drug regulation, software security -- a later document can formally void an e

cool new paper on self-improving agents

cool new paper on self-improving agents // Self-Evolving Agent Protocol // One of the more interesting papers I read this week. (bookmark it if you are an AI dev) The paper introduces Autogenesis, a s

agentsdair-ai--x

CooperDrive: Enhancing Driving Decisions Through Cooperative Perception

arXiv:2604.14454v1 Announce Type: cross Abstract: Autonomous vehicles equipped with robust onboard perception, localization, and planning still face limitations in occlusion and non-line-of-sight (NLO

agentsarxiv-cs-cv

CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas

arXiv:2604.15267v1 Announce Type: cross Abstract: It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite tr

CoPA: Benchmarking Personalized Question Answering with Data-Informed Cognitive Factors

arXiv:2604.14773v1 Announce Type: new Abstract: While LLMs have demonstrated remarkable potential in Question Answering (QA), evaluating personalization remains a critical bottleneck. Existing paradig

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving

arXiv:2512.14098v3 Announce Type: replace Abstract: Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as outp

researcharxiv-cs-lg

Industry

Correct

Correct 99% of people really do not understand abundance as Elon describes it. The fundamental reason is that they don’t understand compound growth. Same people who would probably pick 1 million dolla

industryelon-musk--x

Correcting Suppressed Log-Probabilities in Language Models with Post-Transformer Adapters

arXiv:2604.14174v1 Announce Type: new Abstract: Alignment-tuned language models frequently suppress factual log-probabilities on politically sensitive topics despite retaining the knowledge in their h

Cosine-Similarity Routing with Semantic Anchors for Interpretable Mixture-of-Experts Language Models

arXiv:2509.14255v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models improve efficiency through sparse activation, but their learned gating functions provide limited insight into routin

Industry

Counterpoint: India's smartphone shipments fell 3% YoY in Q1 2026, a six-year low, as price hikes weigh on sales; 80+ smartphone models saw price hikes of ~15% (Abhinav Parmar/Reuters)

Abhinav Parmar / Reuters: Counterpoint: India's smartphone shipments fell 3% YoY in Q1 2026, a six-year low, as price hikes weigh on sales; 80+ smartphone models saw price hikes of ~15% — India's smar

industrytechmeme

Counting Without Numbers and Finding Without Words

arXiv:2603.24470v2 Announce Type: replace-cross Abstract: Every year, 10 million pets enter shelters, separated from their families. Despite desperate searches by both guardians and lost animals, 70%

Create Expert Content: Deploying a Multi-Agent System with Terraform and Cloud Run

model-releasesgoogle-cloud-ai

In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by

CROP: Token-Efficient Reasoning in Large Language Models via Regularized Prompt Optimization

arXiv:2604.14214v1 Announce Type: new Abstract: Large Language Models utilizing reasoning techniques improve task performance but incur significant latency and token costs due to verbose generation. E

agentsarxiv-cs-cl

Cross Paradigm Representation and Alignment Transformer for Image Deraining

model-releasesarxiv-cs-cv

arXiv:2504.16455v2 Announce Type: replace Abstract: Transformer-based networks have achieved strong performance in low-level vision tasks like image deraining by utilizing spatial or channel-wise self

Crowdsourcing of Real-world Image Annotation via Visual Properties

arXiv:2604.14449v1 Announce Type: new Abstract: Recent advances in data-centric artificial intelligence highlight inherent limitations in object recognition datasets. One of the primary issues stems f

safetyarxiv-cs-cv

CSRA: Controlled Spectral Residual Augmentation for Robust Sepsis Prediction

arXiv:2604.14532v1 Announce Type: new Abstract: Accurate prediction of future risk and disease progression in sepsis is clinically important for early warning and timely intervention in intensive care

researcharxiv-cs-lg

Applications

CT-VIR: Continuous-Time Visual-Inertial-Ranging Fusion for Indoor Localization with Sparse Anchors

arXiv:2604.14545v1 Announce Type: new Abstract: Visual-inertial odometry (VIO) is widely used for mobile robot localization, but its long-term accuracy degrades without global constraints. Incorporati

applicationsarxiv-cs-ro

CURA: Clinical Uncertainty Risk Alignment for Language Model-Based Risk Prediction

arXiv:2604.14651v1 Announce Type: new Abstract: Clinical language models (LMs) are increasingly applied to support clinical risk prediction from free-text notes, yet their uncertainty estimates often

CURaTE: Continual Unlearning in Real Time with Ensured Preservation of LLM Knowledge

arXiv:2604.14644v1 Announce Type: new Abstract: The inability to filter out in advance all potentially problematic data from the pre-training of large language models has given rise to the need for me

Hardware

cuRoboV2: Dynamics-Aware Motion Generation with Depth-Fused Distance Fields for High-DoF Robots

arXiv:2603.05493v2 Announce Type: replace Abstract: Effective robot autonomy requires motion generation that is safe, feasible, and reactive. Current methods are fragmented: fast planners output physi

hardwarearxiv-cs-ro

Curvature-Aligned Probing for Local Loss-Landscape Stabilization

model-releasesarxiv-cs-lg

arXiv:2604.14870v1 Announce Type: new Abstract: Local loss-landscape stabilization under sample growth is typically measured either pointwise or through isotropic averaging in the full parameter space

Hardware

DA-Cramming: Enhancing Cost-Effective Language Model Pretraining with Dependency Agreement Integration

arXiv:2311.04799v2 Announce Type: replace Abstract: Pretraining language models is still a challenge for many researchers due to its substantial computational costs. As such, there is growing interest

hardwarearxiv-cs-cl