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Can orbital data centers help justify a massive valuation for SpaceX? | TechCrunch
Ai Startups

Can orbital data centers help justify a massive valuation for SpaceX? | TechCrunch

On the latest episode of TechCrunch’s Equity podcast, we debated Elon Musk's vision for data centers in space.

TechCrunch - AI · 8 min ·
Machine Learning

[D] ICML Rebuttle Acknowledgement

I've received 3 out of 4 acknowledgements, All of them basically are choosing Option A without changing their scores, because their initi...

Reddit - Machine Learning · 1 min ·
Lindner launches Master of Science in AI Management
Ai Startups

Lindner launches Master of Science in AI Management

With an eye towards the evolving business landscape, the Carl H. Lindner College of Business is meeting the moment with the introduction ...

AI News - General · 4 min ·

All Content

[2508.01504] Instruction-based Time Series Editing
Generative Ai

[2508.01504] Instruction-based Time Series Editing

The paper introduces Instruction-based Time Series Editing, a novel approach that allows users to modify time series data using natural l...

arXiv - Machine Learning · 4 min ·
[2505.16308] Beyond All-to-All: Causal-Aligned Transformer with Dynamic Structure Learning for Multivariate Time Series Forecasting
Machine Learning

[2505.16308] Beyond All-to-All: Causal-Aligned Transformer with Dynamic Structure Learning for Multivariate Time Series Forecasting

This article presents a novel approach to multivariate time series forecasting using a Causal Decomposition Transformer (CDT) that learns...

arXiv - Machine Learning · 4 min ·
[2501.18138] B3C: A Minimalist Approach to Offline Multi-Agent Reinforcement Learning
Ai Agents

[2501.18138] B3C: A Minimalist Approach to Offline Multi-Agent Reinforcement Learning

The paper presents B3C, a novel approach to offline multi-agent reinforcement learning that addresses overestimation issues by integratin...

arXiv - Machine Learning · 4 min ·
[2602.12904] Nonparametric Contextual Online Bilateral Trade
Ai Infrastructure

[2602.12904] Nonparametric Contextual Online Bilateral Trade

This paper explores nonparametric contextual online bilateral trade, presenting an algorithm that optimizes trade pricing based on contex...

arXiv - Machine Learning · 3 min ·
[2602.12903] Contextual Online Bilateral Trade
Ai Startups

[2602.12903] Contextual Online Bilateral Trade

This paper explores contextual online bilateral trade, focusing on how agents' valuations depend on context vectors. It presents algorith...

arXiv - Machine Learning · 4 min ·
[2602.12478] Task- and Metric-Specific Signal Quality Indices for Medical Time Series
Ai Infrastructure

[2602.12478] Task- and Metric-Specific Signal Quality Indices for Medical Time Series

The paper introduces a new perturbation-based signal quality index (pSQI) for medical time series, addressing the limitations of existing...

arXiv - Machine Learning · 4 min ·
[2602.12445] RBCorr: Response Bias Correction in Language Models
Llms

[2602.12445] RBCorr: Response Bias Correction in Language Models

The paper presents RBCorr, a method for correcting response biases in language models, demonstrating its effectiveness across various mod...

arXiv - Machine Learning · 3 min ·
[2602.13042] GPTZero: Robust Detection of LLM-Generated Texts
Llms

[2602.13042] GPTZero: Robust Detection of LLM-Generated Texts

GPTZero introduces a robust solution for detecting AI-generated texts, addressing concerns over text authenticity and misinformation in t...

arXiv - Machine Learning · 3 min ·
[2602.13004] Uncertainty in Federated Granger Causality: From Origins to Systemic Consequences
Ai Startups

[2602.13004] Uncertainty in Federated Granger Causality: From Origins to Systemic Consequences

This paper presents a novel methodology for quantifying uncertainty in Federated Granger Causality, addressing limitations in existing al...

arXiv - Machine Learning · 4 min ·
[2602.12744] Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification
Machine Learning

[2602.12744] Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification

This article presents Dynamic Structured Pruning (DSP), an innovative method for optimizing convolutional neural networks in time series ...

arXiv - Machine Learning · 4 min ·
[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs
Llms

[2602.12756] Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs

This paper introduces F-LLM, a control-theoretic framework for stable time series forecasting using large language models, addressing iss...

arXiv - Machine Learning · 4 min ·
[2602.12606] RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
Llms

[2602.12606] RelBench v2: A Large-Scale Benchmark and Repository for Relational Data

RelBench v2 introduces a comprehensive benchmark for relational deep learning, featuring 11 datasets and new predictive tasks, enhancing ...

arXiv - Machine Learning · 4 min ·
[2602.10496] Low-Dimensional Execution Manifolds in Transformer Learning Dynamics: Evidence from Modular Arithmetic Tasks
Machine Learning

[2602.10496] Low-Dimensional Execution Manifolds in Transformer Learning Dynamics: Evidence from Modular Arithmetic Tasks

This paper explores the geometric structure of learning dynamics in transformer models, revealing that training trajectories collapse ont...

arXiv - Machine Learning · 4 min ·
[2602.01157] Deep Time-Series Models Meet Volatility: Multi-Horizon Electricity Price Forecasting in the Australian National Electricity Market
Machine Learning

[2602.01157] Deep Time-Series Models Meet Volatility: Multi-Horizon Electricity Price Forecasting in the Australian National Electricity Market

This paper explores the effectiveness of deep time-series models for forecasting electricity prices in the volatile Australian National E...

arXiv - Machine Learning · 4 min ·
[2512.18080] From Prompt to Product: A Human-Centered Benchmark of Agentic App Generation Systems
Nlp

[2512.18080] From Prompt to Product: A Human-Centered Benchmark of Agentic App Generation Systems

This paper introduces a human-centered benchmark for evaluating agentic app generation systems, comparing platforms like Replit, Bolt, an...

arXiv - AI · 4 min ·
[2510.09717] Provable Training Data Identification for Large Language Models
Llms

[2510.09717] Provable Training Data Identification for Large Language Models

This paper presents a novel approach for identifying training data in large language models, addressing issues of copyright and privacy t...

arXiv - Machine Learning · 4 min ·
[2509.14832] Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization
Machine Learning

[2509.14832] Diffusion-Based Scenario Tree Generation for Multivariate Time Series Prediction and Multistage Stochastic Optimization

The paper presents a Diffusion Scenario Tree (DST) framework for multivariate time series prediction and multistage stochastic optimizati...

arXiv - Machine Learning · 4 min ·
[2508.17742] EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation of EEG Foundation Models
Llms

[2508.17742] EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation of EEG Foundation Models

The paper presents EEG-FM-Bench, a standardized benchmark for evaluating EEG foundation models, addressing inconsistencies in current eva...

arXiv - AI · 4 min ·
[2508.08275] MLLM-CTBench: A Benchmark for Continual Instruction Tuning with Reasoning Process Diagnosis
Llms

[2508.08275] MLLM-CTBench: A Benchmark for Continual Instruction Tuning with Reasoning Process Diagnosis

The paper presents MLLM-CTBench, a benchmark for continual instruction tuning of multimodal large language models, addressing the need fo...

arXiv - AI · 4 min ·
[2503.22968] Redefining Evaluation Standards: A Unified Framework for Evaluating the Korean Capabilities of Language Models
Llms

[2503.22968] Redefining Evaluation Standards: A Unified Framework for Evaluating the Korean Capabilities of Language Models

This article introduces the Haerae Evaluation Toolkit (HRET), a unified framework for evaluating the capabilities of Korean language mode...

arXiv - AI · 4 min ·
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