Jim Cramer Predicts Super Micro (SMCI) Will Go Up
Server hardware firm Super Micro Computer Inc. (NASDAQ:SMCI)’s shares are up by 48% year-to-date and by 15% over the year.
慢半拍也要搶！微軟、Google強攻AI寫程式 力抗Anthropic與OpenAI
生成式AI市場戰火愈演愈烈，自動化寫程式工具正成為Google與微軟（Microsoft）的頭號戰略目標，試圖急速追趕領先者Anthropi...
Latest in Ai
Showing 801-850 of 5249
Jim Cramer Can’t Understand Why NVIDIA (NVDA) Won’t Go Up
AI GPU giant NVIDIA Corporation (NASDAQ:NVDA) is one of Jim Cramer’s favorite stocks even though the shares have remained lackluster this year. Year-to-date, ...
This AI model backdoor attack stays hidden until you customize the model
A new AI model backdoor attack hides in shared models, passing security scans and activating only after a user customizes the model.
Applied Materials (AMAT) Can’t Keep Up With Demand, Says Jim Cramer
Semiconductor manufacturing equipment provider Applied Materials, Inc. (NASDAQ:AMAT) is one of the most crucial stocks in the AI era due to its position at the ...
Intel Computex 2026 Keynote Live Coverage
Closing out Computex's day 2 keynotes is Intel, where CEO Lip-Bu Tan will be outlining Intel's vision for the Intelligence Era and engineering AI hardware acros...
Jim Cramer Discusses Why Micron’s (MU) Important
Memory chip manufacturer Micron Technology, Inc. (NASDAQ:MU) is one of the hottest stocks on Wall Street. Its shares are up by an unbelievable 927% over the pas...
Florida sues OpenAI and Altman over ChatGPT safety concerns
Florida sues OpenAI and CEO Sam Altman over ChatGPT safety concerns, citing risks to minors and public safety.
[2511.07910] Last Layer Logits to Logic: Empowering LLMs with Logic-Consistent Structured Knowledge Reasoning
Abstract page for arXiv paper 2511.07910: Last Layer Logits to Logic: Empowering LLMs with Logic-Consistent Structured Knowledge Reasoning
[2511.08851] Measurement-Driven Early Warning of Reliability Breakdown in 5G NSA Railway Networks
Abstract page for arXiv paper 2511.08851: Measurement-Driven Early Warning of Reliability Breakdown in 5G NSA Railway Networks
[2511.09190] Iterated Population Based Training with Task-Agnostic Restarts
Abstract page for arXiv paper 2511.09190: Iterated Population Based Training with Task-Agnostic Restarts
[2511.10276] RoboBenchMart: Benchmarking Robots in Retail Environment
Abstract page for arXiv paper 2511.10276: RoboBenchMart: Benchmarking Robots in Retail Environment
[2511.12081] From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction
Abstract page for arXiv paper 2511.12081: From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction
[2511.14460] Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning
Abstract page for arXiv paper 2511.14460: Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning
[2606.01800] Multilinguality of Large Language Models From a Structural Perspective
Abstract page for arXiv paper 2606.01800: Multilinguality of Large Language Models From a Structural Perspective
[2606.01801] MetaForge: A Self-Evolving Multimodal Agent that Retrieves, Adapts, and Forges Tools On Demand
Abstract page for arXiv paper 2606.01801: MetaForge: A Self-Evolving Multimodal Agent that Retrieves, Adapts, and Forges Tools On Demand
[2606.01802] MOSS-Audio Technical Report
Abstract page for arXiv paper 2606.01802: MOSS-Audio Technical Report
[2606.01803] OctoT2I: A Self-Evolving Agentic Text-to-Image Router
Abstract page for arXiv paper 2606.01803: OctoT2I: A Self-Evolving Agentic Text-to-Image Router
[2606.01806] ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference
Abstract page for arXiv paper 2606.01806: ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference
[2606.01808] Personalized 3D Myocardial Infarct Geometry Reconstruction from Cine MRI for Cardiac Digital Twins
Abstract page for arXiv paper 2606.01808: Personalized 3D Myocardial Infarct Geometry Reconstruction from Cine MRI for Cardiac Digital Twins
[2606.01810] Token Predictors Are Not Planners: Building Physically Grounded Causal Reasoners
Abstract page for arXiv paper 2606.01810: Token Predictors Are Not Planners: Building Physically Grounded Causal Reasoners
[2606.01811] "I've Seen How This Goes": Characterizing Diversity via Progressive Conditional Surprise
Abstract page for arXiv paper 2606.01811:
[2606.01813] Cost-Aware Diffusion Draft Trees for Speculative Decoding
Abstract page for arXiv paper 2606.01813: Cost-Aware Diffusion Draft Trees for Speculative Decoding
[2606.01830] CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback
Abstract page for arXiv paper 2606.01830: CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback
[2606.01833] Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation
Abstract page for arXiv paper 2606.01833: Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation
[2606.01834] Physics-Guided Attention in a Lightweight TCN for Efficient WiFi CSI-Based Human Activity Recognition
Abstract page for arXiv paper 2606.01834: Physics-Guided Attention in a Lightweight TCN for Efficient WiFi CSI-Based Human Activity Recognition
[2606.01837] Benign Inputs, Harmful Outputs: Cross-Modal Jailbreaking via Distributed Semantic Recomposition
Abstract page for arXiv paper 2606.01837: Benign Inputs, Harmful Outputs: Cross-Modal Jailbreaking via Distributed Semantic Recomposition
[2606.01838] LayerRoute: Input-Conditioned Adaptive Layer Skipping via LoRA Fine-Tuning for Agentic Language Models
Abstract page for arXiv paper 2606.01838: LayerRoute: Input-Conditioned Adaptive Layer Skipping via LoRA Fine-Tuning for Agentic Language Models
[2606.01839] Observation, Not Prediction: Conversation-Level Disaggregated Scheduling for Agentic Serving
Abstract page for arXiv paper 2606.01839: Observation, Not Prediction: Conversation-Level Disaggregated Scheduling for Agentic Serving
[2606.01840] Evaluation of Baseline Methods for IDD-based SSD External Memory Search
Abstract page for arXiv paper 2606.01840: Evaluation of Baseline Methods for IDD-based SSD External Memory Search
[2606.01843] Suppressing Forgery-Specific Shortcuts for Generalizable Deepfake Detection
Abstract page for arXiv paper 2606.01843: Suppressing Forgery-Specific Shortcuts for Generalizable Deepfake Detection
[2606.01844] Decoupled Residual Quantization for Robust Semantic IDs in Recommendation
Abstract page for arXiv paper 2606.01844: Decoupled Residual Quantization for Robust Semantic IDs in Recommendation
[2606.01845] Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses
Abstract page for arXiv paper 2606.01845: Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses
[2606.01945] Beyond Low-Rank: Low-Rank Sparse Prompting via Spiking Neural Network and Prompt Factorization
Abstract page for arXiv paper 2606.01945: Beyond Low-Rank: Low-Rank Sparse Prompting via Spiking Neural Network and Prompt Factorization
[2606.01947] Parameter-Efficient Fine-Tuning of Large Pretrained Models for Instance Segmentation Tasks
Abstract page for arXiv paper 2606.01947: Parameter-Efficient Fine-Tuning of Large Pretrained Models for Instance Segmentation Tasks
[2606.01948] Rank-Constrained Deep Matrix Completion for Group Recommendation
Abstract page for arXiv paper 2606.01948: Rank-Constrained Deep Matrix Completion for Group Recommendation
[2606.01950] Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects
Abstract page for arXiv paper 2606.01950: Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects
[2606.01951] Co-training with Ego-centric Video and Demonstration for Robot Navigation Task
Abstract page for arXiv paper 2606.01951: Co-training with Ego-centric Video and Demonstration for Robot Navigation Task
[2606.01909] Echo: A Joint-Embedding Predictive Architecture for Speaker Diarization and Speech Recognition in a Shared Latent Space
Abstract page for arXiv paper 2606.01909: Echo: A Joint-Embedding Predictive Architecture for Speaker Diarization and Speech Recognition in a Shared Latent Spac...
[2606.01910] Single-Line Drawing Generation via Semantics-Driven Optimization
Abstract page for arXiv paper 2606.01910: Single-Line Drawing Generation via Semantics-Driven Optimization
[2606.01911] Residual Decoder Adapter: ID-Preserving Tokenizer Adaption for Autoregressive Text Rendering
Abstract page for arXiv paper 2606.01911: Residual Decoder Adapter: ID-Preserving Tokenizer Adaption for Autoregressive Text Rendering
[2606.01912] SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
Abstract page for arXiv paper 2606.01912: SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
[2606.01914] Mechanistic Diagnostics of Spatial Lexical Bias in Multimodal Large Language Model Spatial Reasoning
Abstract page for arXiv paper 2606.01914: Mechanistic Diagnostics of Spatial Lexical Bias in Multimodal Large Language Model Spatial Reasoning
[2606.01920] Pool-Select-Refine: Allocation-Aware Generative Dataset Distillation with Soft-Label-Guided Latent Refinement
Abstract page for arXiv paper 2606.01920: Pool-Select-Refine: Allocation-Aware Generative Dataset Distillation with Soft-Label-Guided Latent Refinement
[2606.01923] Resonant Context Anchoring: Decoupling Attention Routing and Signal Gain at Inference Time
Abstract page for arXiv paper 2606.01923: Resonant Context Anchoring: Decoupling Attention Routing and Signal Gain at Inference Time
[2606.01925] QoEReasoner: An Agentic Reasoning Framework for Automated and Explainable QoE Diagnosis in RANs
Abstract page for arXiv paper 2606.01925: QoEReasoner: An Agentic Reasoning Framework for Automated and Explainable QoE Diagnosis in RANs
[2606.01926] Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
Abstract page for arXiv paper 2606.01926: Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
[2606.01927] Scaling LLM Inference Beyond Amdahl`s Limits via Eliminating Non-Scalable Overheads
Abstract page for arXiv paper 2606.01927: Scaling LLM Inference Beyond Amdahl`s Limits via Eliminating Non-Scalable Overheads