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ComPASS: Towards Personalized Agentic Social Support via Tool-Augmented Companionship

arXiv:2604.18356v1 Announce Type: new Abstract: Developing compassionate interactive systems requires agents to not only understand user emotions but also provide diverse, substantive support. While r

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Compiling OpenSCENARIO 2.1 for Scenario-Based Testing in CARLA

DGX agent

arXiv:2604.16452v1 Announce Type: new Abstract: While the ASAM OpenSCENARIO 2.1 Domain-Specific Language (DSL) enables declarative, intent-driven authoring for Scenario-Based Testing (SBT), its integr

researcharxiv-cs-ro

21 Apr 2026

Complex normalizing flows can be information Kahler-Ricci flows

arXiv:2604.17954v1 Announce Type: cross Abstract: We develop interconnections between the complex normalizing flow for data drawn from Borel probability measures on the twofold realification of the co

Composed Vision-Language Retrieval for Skin Cancer Case Search via Joint Alignment of Global and Local Representations

arXiv:2603.09108v2 Announce Type: replace Abstract: Medical image retrieval aims to identify clinically relevant lesion cases to support diagnostic decision making, education, and quality control. In

safetyarxiv-cs-cv

Compositional Steering of Large Language Models with Steering Tokens

arXiv:2601.05062v2 Announce Type: replace Abstract: Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work exte

applicationsarxiv-cs-cl

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding

arXiv:2511.08480v3 Announce Type: replace Abstract: Multimodal Large Language Models advance multimodal representation learning by acquiring transferable semantic embeddings, thereby substantially enh

researcharxiv-cs-cv

Concurrent Criterion Validation of a Validity Screen for LLM Confidence Signals via Selective Prediction

arXiv:2604.17716v1 Announce Type: new Abstract: The validity screen (Cacioli, 2026d, 2026e) classifies LLM confidence signals as Valid, Indeterminate, or Invalid. We test whether these classifications

Hardware

Condense, Don't Just Prune: Enhancing Efficiency and Performance in MoE Layer Pruning

arXiv:2412.00069v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) has garnered significant attention for its ability to scale up neural networks while utilizing the same or even fewer

hardwarearxiv-cs-cl

Conditional Attribution for Root Cause Analysis in Time-Series Anomaly Detection

arXiv:2604.17616v1 Announce Type: new Abstract: Root cause analysis (RCA) for time-series anomaly detection is critical for the reliable operation of complex real-world systems. Existing explanation m

Conditional Evidence Reconstruction and Decomposition for Interpretable Multimodal Diagnosis

arXiv:2604.17030v1 Announce Type: new Abstract: Neurobiological and neurodegenerative diseases are inherently multifactorial, arising from coupled influences spanning genetic susceptibility, brain alt

applicationsarxiv-cs-cv

Conformal Prediction-Based MPC for Stochastic Linear Systems

arXiv:2512.10738v2 Announce Type: replace-cross Abstract: We propose a stochastic model predictive control (MPC) framework for linear systems subject to joint-in-time chance constraints under unknown

researcharxiv-cs-ro

Conformal Risk Control under Non-Monotone Losses: Theory and Finite-Sample Guarantees

arXiv:2604.01502v2 Announce Type: replace-cross Abstract: Conformal risk control (CRC) provides distribution-free guarantees for controlling the expected loss at a user-specified level. Existing theor

ConforNets: Latents-Based Conformational Control in OpenFold3

arXiv:2604.18559v1 Announce Type: cross Abstract: Models from the AlphaFold (AF) family reliably predict one dominant conformation for most well-ordered proteins but struggle to capture biologically r

researcharxiv-cs-lg

ConMeZO: Adaptive Descent-Direction Sampling for Gradient-Free Finetuning of Large Language Models

arXiv:2511.02757v2 Announce Type: replace Abstract: Zeroth-order or derivative-free optimization (MeZO) is an attractive strategy for finetuning large language models (LLMs) because it eliminates the

Conservative Judge J. Michael Luttig is warning that Trump is already preparing to rig the 2026 midterms, not by one single scheme but by a …

Conservative Judge J. Michael Luttig is warning that Trump is already preparing to rig the 2026 midterms, not by one single scheme but by a whole “buffet of options” to throw the election into chaos.

researchyann-lecun--x

Constructive Distortion: Improving MLLMs with Attention-Guided Image Warping

model-releasesarxiv-cs-cv

arXiv:2510.09741v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) often miss small details and spatial relations in cluttered scenes, leading to errors in fine-grained perce

Contact-Rich Robotic Assembly in Construction via Diffusion Policy Learning

arXiv:2511.17774v3 Announce Type: replace Abstract: Fabrication uncertainty arising from tolerance accumulation, material imperfection, and positioning errors remains a critical barrier to automated r

safetyarxiv-cs-ro

Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification

arXiv:2601.06394v3 Announce Type: replace Abstract: Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predic

researcharxiv-cs-cv

Continual Safety Alignment via Gradient-Based Sample Selection

arXiv:2604.17215v1 Announce Type: new Abstract: Large language models require continuous adaptation to new tasks while preserving safety alignment. However, fine-tuning on even benign data often compr

safetyarxiv-cs-lg

Continuous ageing trajectory representations for knee-aware lifetime prediction of lithium-ion batteries across heterogeneous dataset

arXiv:2604.16580v1 Announce Type: new Abstract: Accurate assessment of lithium-ion battery ageing is challenged by cell-to-cell variability, heterogeneous cycling protocols, and limited transferabilit

researcharxiv-cs-lg

Continuous Focus Groups: A Longitudinal Method for Clinical HRI in Autism Care

arXiv:2604.18197v1 Announce Type: cross Abstract: Qualitative methods are important to use alongside quantitative methods to improve Human-Robot Interaction (HRI), yet they are often applied in static

researcharxiv-cs-ro

Continuous Limits of Coupled Flows in Representation Learning

arXiv:2604.16801v1 Announce Type: new Abstract: While modern representation learning relies heavily on global error signals, decentralized algorithms driven by local interactions offer a fundamental d

Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells

arXiv:2604.17548v1 Announce Type: new Abstract: Persistent homology (PH) encodes global information, such as cycles, and is thus increasingly integrated into graph neural networks (GNNs). PH methods i

applicationsarxiv-cs-lg

Industry

Contrary to popular superstition, AES 128 is just fine in a post-quantum world

AES-128 remains secure against quantum computers and does not require key size changes as part of the post-quantum transition. NIST considers AES-128 safe and has made it the security benchmark for po

industryars-technica

Contrastive Analysis of Linguistic Representations in Large Language Model Outputs through Structured Synthetic Data Generation and Abstracted N-gram Associations

arXiv:2604.17398v1 Announce Type: new Abstract: We present a methodological framework to discover linguistic and discursive patterns associated to different social groups through contrastive synthetic

safetyarxiv-cs-cl

Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks

arXiv:2604.17761v1 Announce Type: cross Abstract: Interpretability tools are increasingly used to analyze failures of Large Language Models (LLMs), yet prior work largely focuses on short prompts or t

researcharxiv-cs-cl

Tutorials

ControlAudio: Tackling Text-Guided, Timing-Indicated and Intelligible Audio Generation via Progressive Diffusion Modeling

arXiv:2510.08878v3 Announce Type: replace-cross Abstract: Text-to-audio (TTA) generation with fine-grained control signals, e.g., precise timing control or intelligible speech content, has been explor

tutorialsarxiv-cs-cl

Convergence theory for Hermite approximations under adaptive coordinate transformations

arXiv:2604.16975v1 Announce Type: cross Abstract: Recent work has shown that parameterizing and optimizing coordinate transformations using normalizing flows, i.e., invertible neural networks, can sig

researcharxiv-cs-lg

Cooperative Coevolution versus Monolithic Evolutionary Search for Semi-Supervised Tabular Classification

arXiv:2604.16412v1 Announce Type: cross Abstract: This paper studies semi-supervised tabular classification in the extreme low-label regime using lightweight base learners. The paper proposes a cooper

safetyarxiv-cs-lg

Hardware

Copy-as-Decode: Grammar-Constrained Parallel Prefill for LLM Editing

arXiv:2604.18170v1 Announce Type: new Abstract: LLMs edit text and code by autoregressively regenerating the full output, even when most tokens appear verbatim in the input. We study Copy-as-Decode, a

hardwarearxiv-cs-cl

Copy First, Translate Later: Interpreting Translation Dynamics in Multilingual Pretraining

arXiv:2604.17633v1 Announce Type: new Abstract: Large language models exhibit impressive cross-lingual capabilities. However, prior work analyzes this phenomenon through isolated factors and at sparse

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

model-releasesarxiv-cs-cv

arXiv:2404.03191v3 Announce Type: replace Abstract: Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems resea

Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols

arXiv:2604.18245v1 Announce Type: new Abstract: Large language models are increasingly deployed as protocols: structured multi-call procedures that spend additional computation to transform a baseline

safetyarxiv-cs-lg

COSEARCH: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search

arXiv:2604.17555v1 Announce Type: cross Abstract: Agentic search -- the task of training agents that iteratively reason, issue queries, and synthesize retrieved information to answer complex questions

safetyarxiv-cs-cl

Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR

arXiv:2603.07084v2 Announce Type: replace-cross Abstract: Reward hacking is a form of misalignment in which models overoptimize proxy rewards without genuinely solving the underlying task. Precisely m

researcharxiv-cs-cl

Counterfactual Modeling with Fine-Tuned LLMs for Health Intervention Design and Sensor Data Augmentation

arXiv:2601.14590v2 Announce Type: replace Abstract: Counterfactual explanations (CFEs) provide human-centric interpretability by identifying the minimal, actionable changes required to alter a machine

Covariance-Based Structural Equation Modeling in Small-Sample Settings with p>n

arXiv:2604.16894v1 Announce Type: new Abstract: Factor-based Structural Equation Modeling (SEM) relies on likelihood-based estimation assuming a nonsingular sample covariance matrix, which breaks down

applicationsarxiv-cs-lg

Industry

Cowbell debuts Prime One cyber insurance with AI and quantum risk cover

Cybersecurity insurance provider Cowbell Cyber Inc. today announced the U.S. launch of Cowbell Prime One, a new non-admitted cyber insurance product that is designed for organizations with advanced di

industrysiliconangle

Industry

🟡🔴 Crazy scenes in Lens. The fans invaded the pitch after reaching the Coupe de France final! It's the first time in 28 YEARS that they ha…

RC Lens fans invaded the pitch after their team qualified for the Coupe de France final, marking the club's first appearance in the competition's final in 28 years. The celebration reflected the signi

industryclem-delangue--x

Creating ConLangs to Probe the Metalinguistic Grammatical Knowledge of LLMs

arXiv:2510.07591v3 Announce Type: replace Abstract: We present a system that uses LLMs as a tool in the development of Constructed Languages -- ConLangs, which we call IASC (Interactive Agentic System

CreditDecoding: Accelerating Parallel Decoding in Diffusion Large Language Models with Trace Credit

arXiv:2510.06133v2 Announce Type: replace Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising. In commonly adopted parallel decoding schemes, each step confirms

CRISP: Compressing Redundancy in Chain-of-Thought via Intrinsic Saliency Pruning

arXiv:2604.17297v1 Announce Type: new Abstract: Long Chain-of-Thought (CoT) reasoning is pivotal for the success of recent reasoning models but suffers from high computational overhead and latency. Wh

safetyarxiv-cs-cl

CROC: Evaluating and Training T2I Metrics with Pseudo- and Human-Labeled Contrastive Robustness Checks

arXiv:2505.11314v2 Announce Type: replace-cross Abstract: The assessment of evaluation metrics (meta-evaluation) is crucial for determining the suitability of existing metrics in text-to-image (T2I) g

Cross-Family Speculative Decoding for Polish Language Models on Apple~Silicon: An Empirical Evaluation of Bielik~11B with UAG-Extended MLX-LM

arXiv:2604.16368v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by using a small draft model to propose k candidate tokens for a target model to verify. While effective

Cross-Modal Attention Analysis and Optimization in Vision-Language Models: A Study on Visual Reliability

arXiv:2604.17217v1 Announce Type: new Abstract: Vision-Language Models (VLMs) achieve strong cross-modal performance, yet recent evidence suggests they over-rely on textual descriptions while under-ut

safetyarxiv-cs-cv

Cross-Modal Bayesian Low-Rank Adaptation for Uncertainty-Aware Multimodal Learning

arXiv:2604.16657v1 Announce Type: new Abstract: Large pre-trained language models are increasingly adapted to downstream tasks using parameter-efficient fine-tuning (PEFT), but existing PEFT methods a

Tutorials

Cross-Modal Generation: From Commodity WiFi to High-Fidelity mmWave and RFID Sensing

arXiv:2604.16558v1 Announce Type: new Abstract: AIGC has shown remarkable success in CV and NLP, and has recently demonstrated promising potential in the wireless domain. However, significant data imb

tutorialsarxiv-cs-lg

CrossFlowDG: Bridging the Modality Gap with Cross-modal Flow Matching for Domain Generalization

arXiv:2604.16892v1 Announce Type: new Abstract: Domain generalization (DG) aims to maintain performance under domain shift, which in computer vision appears primarily as stylistic variations that caus

safetyarxiv-cs-cv