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CALM-5G: Event-Level Conformal Risk Control for Predictive Service-Assurance Alarms

arXiv:2610.17962v1 Announce Type: cross Abstract: Predictive service assurance converts forecasts of key performance indicators into alarms, and that conversion decides whether the assurance function

applicationsarxiv-cs-lg

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CALM: Decentralized Control of Cooperative Aerial Manipulation with Multi-Agent Reinforcement Learning

DGX agent

arXiv:2610.18425v1 Announce Type: new Abstract: Cooperative aerial manipulation is difficult under wind, payload motion, and noisy goal broadcasts because multiple Unmanned Aerial Vehicles (UAVs) are

model-releasesarxiv-cs-ro

14 Oct 2026

Can a Frontier VLM Serve as a Robot Policy for Memory-Dependent Manipulation?

model-releasesarxiv-cs-ro

arXiv:2610.17350v1 Announce Type: new Abstract: We use a frozen frontier vision-language model, GPT-6-Astra, directly as the robot policy on RoboMME, a benchmark of 16 memory-dependent manipulation ta

Agents

Can an Agent Learn to Predict Its Own Failure? Outcome-Grounded Confidence Calibration in LLM Agents

arXiv:2610.18614v1 Announce Type: cross Abstract: Controlling an acting LLM agent means deciding, at each step of a long-horizon task, whether to trust its next action, abstain, or hand off to a human

agentsarxiv-cs-lg

Can Machine Learning Potentials Be More Accurate Than the Methods They Are Trained On?

arXiv:2610.18027v1 Announce Type: cross Abstract: Although machine learning potentials (MLPs) generalize across configurational and chemical compound spaces, their accuracy is commonly believed to be

Can Renyi Accountants Beat Lossless Accountants for DP-SGD?

arXiv:2610.17120v1 Announce Type: new Abstract: Recent frameworks in differential privacy (DP), such as privacy loss distributions and f-DP, provide lossless representations of the privacy leakage of

Can Synthetic UAV Benchmarks Be Trusted? Real-Synthetic Validation for UAV Model Selection

arXiv:2610.14647v1 Announce Type: new Abstract: Synthetic UAV imagery can expand pre-deployment test evidence when task-specific Real data are scarce, but visual plausibility or semantic label alignme

Can We Trust This Evaluation? Instance-Level Reliability of LLM-as-a-Judge

arXiv:2610.14029v1 Announce Type: new Abstract: LLM-as-a-judge evaluation commonly aggregates multiple judges' decisions into a majority vote, yet this panel decision process does not guarantee that t

applicationsarxiv-cs-lg

CAPTOR: a vision-language foundation model for Chest-Abdomen-Pelvis Oncologic CT

arXiv:2610.14226v1 Announce Type: new Abstract: Purpose : To develop and evaluate CAPTOR, a deep-learning vision-language foundation model for oncologic chest-abdomen-pelvis (CAP) CT interpretation. M

CartoVec: General-Purpose Location Embeddings from Open Map Data

arXiv:2610.17190v1 Announce Type: new Abstract: Geographic coordinates are common inputs in applied machine learning, but latitude and longitude describe position rather than the surrounding environme

tutorialsarxiv-cs-lg

Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models

arXiv:2610.16813v1 Announce Type: new Abstract: Vision foundation models (VFMs) provide transferable visual representations, but their inference cost limits deployment in many settings. Fine-tuning sp

CAST-ASD: Causal Attention over Speakers and Time for Online Active Speaker Detection

arXiv:2610.14676v1 Announce Type: new Abstract: We present CAST-ASD (Causal Attention over Speakers and Time), a causal joint model for active speaker detection (ASD). Recent ASD models improve perfor

CAST: Real-Time Motion Capture for Any Skeleton Topology

arXiv:2610.14856v1 Announce Type: new Abstract: This paper studies the problem of recovering motion from monocular video, even when the target skeleton topology differs from the subject observed in th

CatPortrait: Taming Video Generative Models for Portrait Animation via In-context Conditioning

arXiv:2610.14957v1 Announce Type: new Abstract: Recent video generative models have shown strong capability in synthesizing high-quality and temporally coherent videos. Yet, adapting them for controll

Local Ai

Causal Discovery Under Hard Selection Bias: A New Robust Score-Matching Approach

arXiv:2610.18075v1 Announce Type: new Abstract: Selection bias is a difficult yet widespread problem in causal discovery, occurring whenever non-random selection processes lead to data that is not rep

local-aiarxiv-cs-lg

Causal Identification from Counterfactual Data: Completeness and Bounding Results

arXiv:2602.23541v3 Announce Type: replace-cross Abstract: Previous work establishing completeness results for counterfactual identification has been circumscribed to the setting where the input data b

CB-Agent: Concept-Based In-Context Learning for Sequential Action Selection

arXiv:2610.14574v1 Announce Type: cross Abstract: In-context learning (ICL) allows large language models to use demonstrations without updating their parameters. For interactive agents, demonstrations

Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completion

arXiv:2610.18871v1 Announce Type: new Abstract: Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors trained on one geometry family frequently

Certified Robustness via Sparse Second-Order Cone Relaxations

arXiv:2610.16016v1 Announce Type: new Abstract: Certified robustness is critical for deploying neural networks in safety-sensitive settings, but computing exact certificates typically requires solving

CESNET-TimeSeries26: A Multi-Year Network Traffic Time Series Dataset for Annual Seasonality, Concept Drift, and Long-Term Anomaly Detection

arXiv:2610.14799v1 Announce Type: cross Abstract: Forecast-based models are fundamental to network traffic management and anomaly detection. However, it is essential to evaluate these forecasting mode

CFG-Policy: Unified Diffusion Policy Learning Framework via Classifier-free Guidance

arXiv:2610.14936v1 Announce Type: cross Abstract: Diffusion policies are increasingly used in robotic control and manipulation, vision-language-action models, and world-model-based agents. Their abili

Chainguard puts Claude Mythos on flaw hunting, secures coding agents and widens Libraries

model-releasessiliconangle

Secure software supply chain solution provider Chainguard Inc. today unveiled a vulnerability-hunting service that uses frontier artificial intelligence models such as Anthropic PBC’s Claude Mythos 5.

ChampionKV: Head-Wise Adaptive Budget Allocation for KV Cache Compression

arXiv:2610.18026v1 Announce Type: new Abstract: Some observation-window-based KV cache compressors use prompt attention to identify important tokens but allocate uniform or predefined budgets across h

ChangeT^3: Evaluating Vision Test-Time Training for Remote Sensing Change Detection

arXiv:2610.15813v1 Announce Type: new Abstract: Bitemporal remote sensing change detection requires representations that preserve spatial detail while capturing contextual information relevant to chan

Channel Match: Calibrating Shape Latents for Few-Step 3D Generation

arXiv:2610.15321v1 Announce Type: new Abstract: Recent native 3D generators achieve high-quality asset creation by modeling structured 3D latents with flow-based transformers, but their high-resolutio

Characterizing and Mitigating Distributional Bias in Physics-Informed Generative Models

arXiv:2610.16582v1 Announce Type: new Abstract: Physics-informed generative models augment a data-fitting objective with residual penalties that encourage physical constraints to hold in generated sam

Characterizing the Separability Gap in Prior-Data Fitted Networks

arXiv:2610.14989v1 Announce Type: new Abstract: Prior-data fitted networks (PFNs) are transformers pretrained on simulated datasets to approximate Bayesian posterior predictive distributions. Standard

tutorialsarxiv-cs-lg

Chasing Label Shifters: A Change-Aware Framework for Dynamic Graph Node Classification

arXiv:2610.17582v1 Announce Type: new Abstract: Entities in real-world systems often evolve over time: users shift between information consumption patterns, researchers migrate between fields, and fir

applicationsarxiv-cs-lg

ChatGPT and basically the entire internet has become an intervention every time sadness is expressed

But meanwhile the numbers of suicides and self-harming are rising. Interesting that is implanted into algorithms everywhere. Why? Why if a person is researching the topic on YT, on NDE's for example w

tutorialsr-chatgpt

Industry

ChatGPT changed its HTML structure and broke some extensions AI Memory Vault is still working

Recently, ChatGPT changed parts of its HTML/DOM structure. Some older selectors, like data-message-author-role, are no longer available in certain versions of the interface.This can break Chrome exten

industryr-chatgpt

Checking the Checkers: A Synthesis of Verifier Noise and Robustness in RLVR

arXiv:2610.17824v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a principal recipe for improving the reasoning of large language models (LLMs). It rest

ChemExplain: A Multimodal Benchmark for Explanatory Chemical Reasoning

arXiv:2610.17183v1 Announce Type: cross Abstract: Current chemistry benchmarks primarily evaluate outcome prediction or reaction pathway generation, but rarely test whether a model can explain why an

ChronoScribe: Semantic-Numerical Specialization for Instruction-Driven Time Series Forecasting

arXiv:2610.16345v1 Announce Type: cross Abstract: Recent advances in instruction-driven time series forecasting highlight a fundamental tension: systems must simultaneously master natural-language ins

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

ChunkAct: Action Chunking for Agentic Robotics

arXiv:2610.18874v1 Announce Type: cross Abstract: Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action

CineMem: Attention-Aligned Fine-grained Memory Retrieval for Multi-Shot Long Video Generation

arXiv:2610.17926v1 Announce Type: new Abstract: Autoregressive video generation relies on memory retrieval to model long-range dependencies. This capability becomes particularly critical for multi-sho

CineRecon: Benchmarking Frontier Models for Agentic Cinematic Reconstruction

arXiv:2610.16577v1 Announce Type: new Abstract: Reconstructing reference videos as editable dynamic 3D scenes is an important path toward controllable video generation for filmmaking: these scenes pro

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

arXiv:2506.17585v4 Announce Type: replace-cross Abstract: Large language models can answer questions correctly and still hallucinate their citations. Most citation systems address this by retrieving d

Agents

CityCode: Building Agent-Operable 3D Cities from Sparse Aerial Observations

arXiv:2610.18342v1 Announce Type: new Abstract: Urban spatial intelligence calls for 3D cities that agents can measure, interpret, and modify across successive tasks. Maintaining such cities as persis

agentsarxiv-cs-cv

CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks

arXiv:2610.15327v1 Announce Type: cross Abstract: Removing audio can shift a visual predictor's output without showing whether the task uses the intended audio information. We introduce Conditional In

Class-Conditional Conformal Prediction for Signal Temporal Logic Inference with Many Classes

arXiv:2610.14352v1 Announce Type: new Abstract: Signal Temporal Logic (STL) inference provides interpretable formulas for time series classification. For multiclass classification, however, accurate p

ClearNav: Perception-Aligned Quadrotor Flight Using Differential-Physics

arXiv:2610.17419v1 Announce Type: cross Abstract: Autonomous quadrotor flight in cluttered environment is an key capability for tasks like inspection and search. Navigation policies trained in simulat

Clinical value claims in multimodal AI outpace supporting evidence

arXiv:2610.14395v1 Announce Type: new Abstract: Multimodal prediction models add a data source, such as imaging or an assay, to clinical information, and health systems must decide whether that added

CLNO: Conservative Local Neural Operator for Compressible Flow Prediction

arXiv:2610.16040v1 Announce Type: cross Abstract: We propose a conservative local neural operator (CLNO) for accurate and generalizable autoregressive prediction of compressible flows. Building upon t

CloneOT: predicting clone-specific perturbation responses with lineage-supervised neural inverse optimal transport

arXiv:2610.16093v1 Announce Type: cross Abstract: Predicting single-cell perturbation responses requires mapping between two unpaired populations of cells measured before and after the perturbation. O

tutorialsarxiv-cs-lg

Closing the Estimation Gap: Training-Free Transductive Inference for Cross-Domain Few-Shot Action Recognition

arXiv:2610.18209v1 Announce Type: new Abstract: Cross-domain few-shot action recognition (CD-FSAR) aims to recognise unseen action classes in a target domain from a handful of labelled videos. Despite

ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion

arXiv:2610.16293v1 Announce Type: new Abstract: Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicke

ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction

arXiv:2610.14200v1 Announce Type: cross Abstract: We introduce ClothCode, a unified generative framework for garment state estimation and action-conditioned dynamics prediction in a shared discrete co

applicationsarxiv-cs-cv