All entries

CART: Context-Aware Terrain Adaptation using Temporal Sequence Selection for Legged Robots

arXiv:2604.14344v1 Announce Type: new Abstract: Animals in nature combine multiple modalities, such as sight and feel, to perceive terrain and develop an understanding of how to walk on uneven terrain

tutorialsarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Catching Every Ripple: Enhanced Anomaly Awareness via Dynamic Concept Adaptation

DGX agent

arXiv:2604.14726v1 Announce Type: new Abstract: Online anomaly detection (OAD) plays a pivotal role in real-time analytics and decision-making for evolving data streams. However, existing methods ofte

model-releasesarxiv-cs-lg

17 Apr 2026

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding

arXiv:2601.21262v3 Announce Type: replace Abstract: Although Multimodal Large Language Models (MLLMs) have shown remarkable potential in Visual Document Retrieval (VDR) through generating high-quality

tutorialsarxiv-cs-cl

CAVERS: Multimodal SLAM Data from a Natural Karstic Cave with Ground Truth Motion Capture

model-releasesarxiv-cs-ro

arXiv:2604.15052v1 Announce Type: new Abstract: Autonomous robots operating in natural karstic caves face perception and navigation challenges that are qualitatively distinct from those encountered in

Agents

CCCE: A Continuous Code Calibration Engine for Autonomous Enterprise Codebase Maintenance via Knowledge Graph Traversal and Adaptive Decision Gating

arXiv:2604.13102v1 Announce Type: cross Abstract: Enterprise software organizations face an escalating challenge in maintaining the integrity, security, and freshness of codebases that span hundreds o

agentsarxiv-cs-ai

Industry

CEO of blacklisted Anthropic is going to the White House

Anthropic CEO Dario Amodei visited the White House on April 17 for a high-stakes meeting with White House Chief of Staff Susie Wiles while his AI company battles the Trump administration in court over

industryr-chatgpt

Industry

Cerebras files to go public on Nasdaq and reports 510M in 2025 revenue, up 76% YoY, with a net income of 87.9M, up from a $485M net loss in 2024 (Jordan Novet/CNBC)

Jordan Novet / CNBC: Cerebras files to go public on Nasdaq and reports 510M in 2025 revenue, up 76% YoY, with a net income of 87.9M, up from a $485M net loss in 2024 — Cerebras, a producer of chips th

industrytechmeme

Certified and accurate computation of function space norms of deep neural networks

arXiv:2603.06431v2 Announce Type: replace-cross Abstract: Neural network methods for PDEs require reliable error control in function space norms. However, trained neural networks can typically only be

researcharxiv-cs-lg

Chain-of-Glimpse: Search-Guided Progressive Object-Grounded Reasoning for Video Understanding

arXiv:2604.14692v1 Announce Type: new Abstract: Video understanding requires identifying and reasoning over semantically discriminative visual objects across frames, yet existing object-agnostic solut

tutorialsarxiv-cs-cv

Chain of Modality: From Static Fusion to Dynamic Orchestration in Omni-MLLMs

arXiv:2604.14520v1 Announce Type: new Abstract: Omni-modal Large Language Models (Omni-MLLMs) promise a unified integration of diverse sensory streams. However, recent evaluations reveal a critical pe

safetyarxiv-cs-cv

Challenges in Translating Technical Lectures: Insights from the NPTEL

arXiv:2602.08698v2 Announce Type: replace Abstract: This study examines the practical applications and methodological implications of Machine Translation in Indian Languages, specifically Bangla, Mala

Chaotic CNN for Limited Data Image Classification

arXiv:2604.14645v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) often exhibit poor generalisation in limited training data scenarios due to overfitting and insufficient feature di

ChatSVA: Bridging SVA Generation for Hardware Verification via Task-Specific LLMs

model-releasesarxiv-cs-ai

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

Tools

china discount is real, damn

This post likely discusses the 'China discount' phenomenon, where Chinese companies or products are priced significantly lower than Western equivalents, examining whether this cost advantage is genuin

toolsswyx--x

Industry

China's smartphone shipments declined 4% YoY in Q1 amid memory shortages; Huawei's shipments grew 2% YoY for a 20% market share, iPhone grew 20% for a 19% share (Ivan Lam/Counterpoint Research)

Ivan Lam / Counterpoint Research: China's smartphone shipments declined 4% YoY in Q1 amid memory shortages; Huawei's shipments grew 2% YoY for a 20% market share, iPhone grew 20% for a 19% share — Iva

industrytechmeme

Applications

Chinese Essay Rhetoric Recognition Using LoRA, In-context Learning and Model Ensemble

arXiv:2604.14167v1 Announce Type: new Abstract: Rhetoric recognition is a critical component in automated essay scoring. By identifying rhetorical elements in student writing, AI systems can better as

applicationsarxiv-cs-cl

Chinese Language Is Not More Efficient Than English in Vibe Coding: A Preliminary Study on Token Cost and Problem-Solving Rate

arXiv:2604.14210v1 Announce Type: new Abstract: A claim has been circulating on social media and practitioner forums that Chinese prompts are more token-efficient than English for LLM coding tasks, po

Chronological Knowledge Retrieval: A Retrieval-Augmented Generation Approach to Construction Project Documentation

arXiv:2604.14169v1 Announce Type: new Abstract: In large-scale construction projects, the continuous evolution of decisions generates extensive records, most often captured in meeting minutes. Since d

CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning

arXiv:2604.14519v1 Announce Type: cross Abstract: Catastrophic forgetting remains a fundamental challenge in continual learning, in which models often forget previous knowledge when fine-tuned on a ne

Class Unlearning via Depth-Aware Removal of Forget-Specific Directions

model-releasesarxiv-cs-cv

arXiv:2604.15166v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted knowledge from a trained model without the cost of retraining from scratch. In class unlearning, however, red

Claude Opus 4.7 on AI Gateway

model-releasesvercel-blog

Claude Opus 4.7 is now available through Vercel's AI Gateway, Anthropic's latest large language model offering integration with Vercel's platform for developers. This enables developers to access Clau

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

safetyarxiv-cs-cl

CLion: Efficient Cautious Lion Optimizer with Enhanced Generalization

model-releasesarxiv-cs-lg

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

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

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

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

safetyarxiv-cs-cl

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

Agents

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

safetyarxiv-cs-cl

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