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Choosing Between PCA and t-SNE for Visualization

For data scientists, working with high-dimensional data is part of daily life...

Chinese tech workers are starting to train their AI doubles–and pushing back

Tech workers in China are being instructed by their bosses to train AI agents to...

Chinese Morph Resolution in E-commerce Live Streaming Scenarios

arXiv:2512.23280v1 Announce Type: new Abstract: E-commerce live streaming in China, particularly on platforms like Douyin...

CHEER-Ekman: Fine-grained Embodied Emotion Classification

arXiv:2506.01047v1 Announce Type: new Abstract: Emotions manifest through physical experiences and bodily reactions, yet identifying...

ChatGPT Group Chats are here … but not for everyone (yet)

It was originally found in leaked code and publicized by AI influencers on X, but...

ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding

arXiv:2509.17481v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have recently demonstrated remarkable progress, yet...

ChartGaze: Enhancing Chart Understanding in LVLMs with Eye-Tracking Guided Attention Refinement

arXiv:2509.13282v1 Announce Type: new Abstract: Charts are a crucial visual medium for communicating and representing...

Character-aware Transformers Learn an Irregular Morphological Pattern Yet None Generalize Like Humans

arXiv:2602.14100v1 Announce Type: new Abstract: Whether neural networks can serve as cognitive models of morphological...

ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering

arXiv:2508.21010v1 Announce Type: cross Abstract: Existing Causal-Why Video Question Answering (VideoQA) models often struggle with...

Chai Discovery Team Releases Chai-2: AI Model Achieves 16% Hit Rate in De Novo Antibody Design

TLDR: Chai Discovery Team introduces Chai-2, a multimodal AI model that enables zero-shot de novo...

Cerebras Releases MiniMax-M2-REAP-162B-A10B: A Memory Efficient Version of MiniMax-M2 for Long Context Coding Agents

Cerebras has released MiniMax-M2-REAP-162B-A10B, a compressed Sparse Mixture-of-Experts (SMoE) Causal Language Model derived from MiniMax-M2...

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