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Cognitive World Models for Process-Level Social Influence Evaluation

arXiv:2606.29495v1 Announce Type: new Abstract: Social influence dialogue changes user behavior by altering internal cognitive states. The central evaluation question is whether the user's beliefs, de

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CoGS: Compositional Dynamic Human-Object Scenes Gaussian Splatting from Monocular Video

DGX agent

arXiv:2606.28820v1 Announce Type: new Abstract: Reconstructing dynamic human--object interaction scenes from monocular video is difficult because the human, manipulated object, and background obey dif

model-releasesarxiv-cs-cv

30 Jun 2026

CogSENet: Blind Image Deblurring with Blur-Conditioned Semantic Routing and Explicit Frequency Fusion

arXiv:2606.30030v1 Announce Type: new Abstract: Blind image deblurring demands the recovery of high-fidelity details and coherent structures from complex, unknown degradations. Current blind image deb

applicationsarxiv-cs-cv

COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies

arXiv:2606.30479v1 Announce Type: cross Abstract: Mitigating an observed adversary in an enterprise network typically takes weeks of expert work: an analyst derives a mitigation tailored to that adver

Local Ai

CollabOD: Collaborative Multi-Backbone with Cross-scale Vision for UAV Small Object Detection

arXiv:2603.05905v2 Announce Type: replace Abstract: Small object detection in unmanned aerial vehicle (UAV) imagery is challenging because high-altitude viewpoints produce severe scale variation, weak

local-aiarxiv-cs-cv

Collective cooperation without individual fidelity in LLM agents

arXiv:2606.30454v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as agents in simulations of social systems, yet it remains unclear when their behavior can be inter

CoLR-Det: Collaborative Latent Restoration for Small Object Detection in Low-Resolution Remote Sensing Images

arXiv:2601.12507v2 Announce Type: replace Abstract: Low-resolution remote sensing small object detection is limited by both missing visual details and the ambiguity of how details serve detection. Exi

ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models

arXiv:2606.28719v1 Announce Type: new Abstract: Test-time adaptation (TTA) of vision-language models (VLMs) is essential for their robust deployment in dynamic, real-world environments. However, exist

Common challenge that will come up in the near future is capturing the gains of greater AI intelligence in organizations. High human capital…

applicationsethan-mollick--x

Common challenge that will come up in the near future is capturing the gains of greater AI intelligence in organizations. High human capital firms need to be set up to benefit from their high-quality

Tutorials

Comparing Chatbot Performance Enhanced with Persistent Homology

arXiv:2606.29857v1 Announce Type: new Abstract: Chatbots have become increasingly prevalent across various domains, offering automated assistance in many areas, especially mental health support. The t

tutorialsarxiv-cs-lg

Comparing Human and Automatic Recognition of Dutch Dysarthric Continuous Speech: A Case Study

arXiv:2606.30237v1 Announce Type: new Abstract: In our goal to develop personalised dysarthric speech recognition (DSR) models, this study compared the recognition performances of human listeners and

applicationsarxiv-cs-cl

COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models

arXiv:2606.28696v1 Announce Type: new Abstract: Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models rem

Complementary RL: Towards Efficient Experience-Driven Agent Learning

arXiv:2603.17621v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for training LLM-based agents, yet remains limited by low sample efficiency, st

safetyarxiv-cs-cl

Complete virtual unwrapping and reading of a rolled Herculaneum papyrus

arXiv:2606.29085v1 Announce Type: cross Abstract: The carbonized papyri from Herculaneum preserve the only large-scale library to survive from classical antiquity, but many unopened rolls remain unrea

Compositional Dynamics in Learning and Mechanics

arXiv:2606.28984v1 Announce Type: cross Abstract: We give a single compositional setting in which gradient-based learning and Hamiltonian-style mechanics appear as functorial semantics. The syntax is

Compressed Sensing for Capability Localization in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2603.03335v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit a wide range of capabilities, including mathematical reasoning, code generation, and linguistic behaviors. We s

ConCent: Contact-Centric Real-to-Sim-to-Real Learning from One Demonstration

arXiv:2606.30268v1 Announce Type: new Abstract: Sim-to-real policy transfer -- deploying policies trained in simulation in the real world -- is a promising paradigm for scaling robot manipulation with

safetyarxiv-cs-ro

Concentration bounds on response-based vector embeddings of black-box generative models

arXiv:2511.08307v2 Announce Type: replace-cross Abstract: Generative models, such as large language models or text-to-image diffusion models, can generate relevant responses to user-given queries. Res

researcharxiv-cs-lg

Concept Removal Guidance: Evidence-Calibrated Negative Guidance for Safe Diffusion Sampling

arXiv:2606.29801v1 Announce Type: new Abstract: Text-to-image diffusion models remain vulnerable to adversarial prompts that elicit disallowed content, motivating reliable inference-time controls. A p

safetyarxiv-cs-cv

Hardware

ConCise: Training-Free Conclusion-Chain State Compression for Cost-Efficient Multi-Step RAG Services

arXiv:2606.28361v1 Announce Type: cross Abstract: Multi-step retrieval-augmented generation (RAG) has been widely deployed as LLM-powered web services for complex question answering, where iterative r

hardwarearxiv-cs-ai

Tutorials

Confidence-feedback-weighted graph matching network: online-offline laser-induced damage site matching under complex interference

arXiv:2606.29255v1 Announce Type: cross Abstract: Online inspection images of final optics in high-power laser facilities contain pseudo-damage sites that closely resemble true damage sites. Determini

tutorialsarxiv-cs-ai

Conformal Prediction with Macro-Coverage Guarantees

arXiv:2606.28598v1 Announce Type: cross Abstract: Prediction sets should have high coverage to be useful, but some coverage notions are more practically relevant than others. In the classification set

researcharxiv-cs-lg

Connectivity Estimation using Stochastic Graph Heat Modelling

arXiv:2606.29098v1 Announce Type: cross Abstract: A growing number of techniques leverage the spatial structures that underlie many real-world datasets. Despite these advances, the complementary task

applicationsarxiv-cs-lg

Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction

arXiv:2606.30035v1 Announce Type: new Abstract: Free-viewing gaze data provides a rich, task-free window into human visual attention. Conventional exploratory data analysis of the data provides user a

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning

arXiv:2606.29812v1 Announce Type: new Abstract: Inductive biases steer learning toward generalizable solutions by encoding task structure. In this work, we identify a crucial missing bias in MLLMs: cr

safetyarxiv-cs-cv

Constrained Tabular Diffusion for Finance

arXiv:2606.28674v1 Announce Type: cross Abstract: Generative models in finance face the dual challenge of producing realistic data while satisfying strict regulatory and economic objectives, a require

applicationsarxiv-cs-ai

Contact-Anchored Proprioceptive Odometry for Legged and Wheel-Legged Robots

arXiv:2602.17393v3 Announce Type: replace Abstract: Reliable odometry for legged robots without cameras or LiDAR remains challenging due to IMU drift and noisy joint velocity sensing. This paper prese

researcharxiv-cs-ro

Agents

Context engineering has its own track at the @aiDotEngineer World's Fair this year. 🎉 I've respected what @swyx and the @latentspacepod te…

Context engineering has its own track at the @aiDotEngineer World's Fair this year. 🎉 I've respected what @swyx and the @latentspacepod team have been building for years — and I'm pumped to be a part

agentsswyx--x

Tutorials

Contrastive vision-language learning with paraphrasing and negation

arXiv:2511.16527v2 Announce Type: replace Abstract: Contrastive vision-language models continue to be the dominant approach for image-text retrieval. Contrastive Language-Image Pre-training (CLIP) tra

tutorialsarxiv-cs-cv

Convergence of Continual Learning in Homogeneous Deep Networks

arXiv:2606.30559v1 Announce Type: new Abstract: We characterize weakly regularized continual classification in homogeneous models as sequential projections onto task margin sets. This result generaliz

researcharxiv-cs-lg

Conversational analytics in BigQuery brings trusted agentic reasoning to everyone

model-releasesgoogle-cloud-ai

Businesses run on fast decisions, but the teams who hold the answers are often buried under a backlog of routine requests, leaving users waiting in line for insights they need now. Today, we are bring

Conversational Domain Adaptation of IndicTrans2 across 21 Indic Languages via Experience Replay and Model Soups

arXiv:2606.29024v1 Announce Type: new Abstract: IndicTrans2 is the strongest open English to Indic translation system, but like most systems it is trained on general text and tends to sound stiff on c

researcharxiv-cs-cl

Conversational Query Engine for Mixed-Modality Heterogeneous Enterprise Data Sources

arXiv:2606.28370v1 Announce Type: cross Abstract: Enterprise business intelligence queries span structured warehouses and unstructured document repositories -- modalities with fundamentally different

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level cod…

Cool new paper from NVIDIA. Looks like agentic coding is moving into hardware design. HORIZON treats hardware design as repository-level code evolution. A Markdown harness becomes a project pack with

model-releasesdair-ai--x

CORE: Common Outcome Regularities from Action-Free Visual Demonstrations for Robot Manipulation

arXiv:2606.29517v1 Announce Type: new Abstract: Robot imitation learning often relies on costly robot demonstrations, while abundant action-free visual demonstrations, such as human videos, are diffic

safetyarxiv-cs-ro

Core dump epidemiology: fixing an 18-year-old bug

This article describes OpenAI's investigation and resolution of a longstanding bug in their data infrastructure that had persisted for 18 years, likely related to how core dumps (system memory snapsho

model-releasesopenai

Agents

CORE Planner: Contextual-memory Oriented Reinforcement-learning in Unknown Environments for Robot Navigation

arXiv:2606.29222v1 Announce Type: new Abstract: Autonomous navigation in unknown environments requires a robot to efficiently reach a predefined goal while exploring without prior maps. Although progr

agentsarxiv-cs-ro

Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs

arXiv:2606.28574v1 Announce Type: cross Abstract: When a large language model (LLM) codes a construct in text as a human annotator would, that agreement makes the LLM a reliable coder. Yet reliability

CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

model-releasesarxiv-cs-cl

arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasin

CoSPlan: Corrective Sequential Planning via Scene Graph Incremental Updates

model-releasesarxiv-cs-cv

arXiv:2512.10342v3 Announce Type: replace Abstract: Vision Language Models (VLMs) have shown promising planning capabilities, yet their success remains confined to the text domain, leaving visual deci

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

arXiv:2511.02734v3 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability

CouCE: A Unified Causal Framework for Debiased Deep Metric Learning

arXiv:2606.30365v1 Announce Type: new Abstract: Deep Metric Learning (DML) often struggles with zero-shot generalization because standard objectives inherently capture what co-occurs rather than what

Agents

Couchbase’s AI Data Plane aims to turn fragmented data into real enterprise agent memory

Couchbase Inc. is trying to solve one of the hardest problems in enterprise artificial intelligence today: turning brittle, chat-style pilots into production-grade agents capable of remembering, reaso

agentssiliconangle

Counterfactual Residual Data Augmentation for Regression

arXiv:2606.28460v1 Announce Type: cross Abstract: Data-driven modeling in real-world regression tasks often suffers from limited training samples, high collection costs, and noisy observations. Inspir

Coverage-Driven KV Cache Eviction for Efficient and Improved Inference of LLM

arXiv:2606.29563v1 Announce Type: cross Abstract: Large language models (LLMs) excel at complex tasks like question answering and summarization, thanks to their ability to handle long-context inputs.

Covering the Unseen: Information Demand Coverage Optimization for Retrieval-Augmented Generation

arXiv:2606.29328v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically treats context selection as ranking chunks against a single query embedding. This assumption breaks dow

CRAFT: Counterfactual Credit Assignment from Free Sibling Rollouts for Self-Distilled Agentic Reinforcement Learning

arXiv:2606.29476v1 Announce Type: cross Abstract: Self-distilled agentic reinforcement learning augments trajectory-level reward with a token-level distillation loss, using as its teacher the same pol

safetyarxiv-cs-ai

Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies

arXiv:2606.29898v1 Announce Type: cross Abstract: Real-world evaluation is the gold standard for robot policies because it tests them against the physical conditions and deployment challenges they are

safetyarxiv-cs-ai