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OpenAI, not yet public, raises $3B from retail investors in monster $122B fund raise | TechCrunch
Ai Infrastructure

OpenAI, not yet public, raises $3B from retail investors in monster $122B fund raise | TechCrunch

OpenAI's latest funding round, led by Amazon, Nvidia, and SoftBank, values the AI lab at $852 billion as it nears an IPO.

TechCrunch - AI · 4 min ·
You can now use ChatGPT with Apple’s CarPlay | The Verge
Llms

You can now use ChatGPT with Apple’s CarPlay | The Verge

ChatGPT is now accessible from your CarPlay dashboard if you have iOS 26.4 or newer and the latest version of the ChatGPT app.

The Verge - AI · 3 min ·
Yupp shuts down after raising $33M from a16z crypto's Chris Dixon | TechCrunch
Machine Learning

Yupp shuts down after raising $33M from a16z crypto's Chris Dixon | TechCrunch

Less than a year after launching, with checks from some of the biggest names in Silicon Valley, crowdsourced AI model feedback startup Yu...

TechCrunch - AI · 4 min ·

All Content

[2602.21926] Bridging Through Absence: How Comeback Researchers Bridge Knowledge Gaps Through Structural Re-emergence
Machine Learning

[2602.21926] Bridging Through Absence: How Comeback Researchers Bridge Knowledge Gaps Through Structural Re-emergence

This article explores the role of 'comeback researchers'—those who return to academia after a hiatus—in bridging knowledge gaps and enhan...

arXiv - Machine Learning · 4 min ·
[2602.21766] RAMSeS: Robust and Adaptive Model Selection for Time-Series Anomaly Detection Algorithms
Machine Learning

[2602.21766] RAMSeS: Robust and Adaptive Model Selection for Time-Series Anomaly Detection Algorithms

The RAMSeS framework enhances time-series anomaly detection by combining a stacking ensemble with adaptive model selection, optimizing pe...

arXiv - Machine Learning · 3 min ·
[2602.21721] Private and Robust Contribution Evaluation in Federated Learning
Machine Learning

[2602.21721] Private and Robust Contribution Evaluation in Federated Learning

This paper presents novel methods for evaluating contributions in federated learning while ensuring privacy and robustness, addressing vu...

arXiv - Machine Learning · 4 min ·
[2602.21265] ToolMATH: A Math Tool Benchmark for Realistic Long-Horizon Multi-Tool Reasoning
Llms

[2602.21265] ToolMATH: A Math Tool Benchmark for Realistic Long-Horizon Multi-Tool Reasoning

ToolMATH introduces a benchmark for evaluating tool-augmented language models in realistic multi-tool environments, focusing on long-hori...

arXiv - Machine Learning · 4 min ·
[2602.21693] TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts
Machine Learning

[2602.21693] TiMi: Empower Time Series Transformers with Multimodal Mixture of Experts

The paper introduces TiMi, a novel approach that enhances time series forecasting by integrating multimodal data through a Mixture of Exp...

arXiv - Machine Learning · 4 min ·
[2602.21498] Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
Ai Startups

[2602.21498] Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting

The paper presents ReIMTS, a new approach for forecasting irregular multivariate time series by preserving original timestamps and captur...

arXiv - Machine Learning · 3 min ·
[2602.21297] Robust AI Evaluation through Maximal Lotteries
Llms

[2602.21297] Robust AI Evaluation through Maximal Lotteries

The paper proposes a new method for evaluating AI models using robust lotteries, addressing limitations of traditional pairwise compariso...

arXiv - Machine Learning · 3 min ·
[2511.06899] RPTS: Tree-Structured Reasoning Process Scoring for Faithful Multimodal Evaluation
Llms

[2511.06899] RPTS: Tree-Structured Reasoning Process Scoring for Faithful Multimodal Evaluation

The paper presents the Reasoning Process Tree Score (RPTS), a novel metric for evaluating reasoning in Large Vision-Language Models (LVLM...

arXiv - AI · 4 min ·
[2510.03255] SciTS: Scientific Time Series Understanding and Generation with LLMs
Llms

[2510.03255] SciTS: Scientific Time Series Understanding and Generation with LLMs

The paper introduces SciTS, a benchmark for understanding and generating scientific time series data using large language models (LLMs), ...

arXiv - Machine Learning · 4 min ·
[2509.23744] Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning
Llms

[2509.23744] Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning

This article explores the foundational bottlenecks in multimodal reasoning, highlighting how additional modalities can enhance or hinder ...

arXiv - AI · 4 min ·
[2509.23597] Characteristic Root Analysis and Regularization for Linear Time Series Forecasting
Machine Learning

[2509.23597] Characteristic Root Analysis and Regularization for Linear Time Series Forecasting

This paper explores the effectiveness of linear models for time series forecasting, focusing on characteristic roots and their impact on ...

arXiv - Machine Learning · 4 min ·
[2507.14206] A Comprehensive Benchmark for Electrocardiogram Time-Series
Machine Learning

[2507.14206] A Comprehensive Benchmark for Electrocardiogram Time-Series

This article presents a comprehensive benchmark for electrocardiogram (ECG) time-series analysis, highlighting its unique characteristics...

arXiv - Machine Learning · 4 min ·
[2503.01927] QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation
Machine Learning

[2503.01927] QCS-ADME: Quantum Circuit Search for Drug Property Prediction with Imbalanced Data and Regression Adaptation

The paper presents QCS-ADME, a novel quantum circuit search framework for predicting drug properties, addressing challenges in imbalanced...

arXiv - Machine Learning · 4 min ·
[2411.03941] Modular Deep Learning for Multivariate Time-Series: Decoupling Imputation and Downstream Tasks
Machine Learning

[2411.03941] Modular Deep Learning for Multivariate Time-Series: Decoupling Imputation and Downstream Tasks

This paper proposes a modular approach to deep learning for multivariate time-series data, separating imputation from downstream tasks to...

arXiv - Machine Learning · 4 min ·
[2406.17115] Measuring the Measurers: Quality Evaluation of Hallucination Benchmarks for Large Vision-Language Models
Llms

[2406.17115] Measuring the Measurers: Quality Evaluation of Hallucination Benchmarks for Large Vision-Language Models

This article evaluates the quality of hallucination benchmarks for Large Vision-Language Models (LVLMs) and introduces a new framework fo...

arXiv - AI · 4 min ·
[2510.19139] A Multi-faceted Analysis of Cognitive Abilities: Evaluating Prompt Methods with Large Language Models on the CONSORT Checklist
Llms

[2510.19139] A Multi-faceted Analysis of Cognitive Abilities: Evaluating Prompt Methods with Large Language Models on the CONSORT Checklist

This paper evaluates the cognitive abilities of large language models (LLMs) in assessing clinical trial reporting according to CONSORT s...

arXiv - AI · 4 min ·
[2602.22207] Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets
Llms

[2602.22207] Recovered in Translation: Efficient Pipeline for Automated Translation of Benchmarks and Datasets

The paper presents an automated framework for translating benchmarks and datasets for multilingual Large Language Model evaluation, addre...

arXiv - Machine Learning · 3 min ·
[2602.22107] Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
Machine Learning

[2602.22107] Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection

This paper examines how different validation criteria for model parameter selection impact test performance in neural classifiers, reveal...

arXiv - Machine Learning · 4 min ·
[2602.22066] DualWeaver: Synergistic Feature Weaving Surrogates for Multivariate Forecasting with Univariate Time Series Foundation Models
Llms

[2602.22066] DualWeaver: Synergistic Feature Weaving Surrogates for Multivariate Forecasting with Univariate Time Series Foundation Models

The paper presents DualWeaver, a novel framework that enhances multivariate forecasting using univariate time series foundation models th...

arXiv - Machine Learning · 3 min ·
[2602.21800] An Evaluation of Context Length Extrapolation in Long Code via Positional Embeddings and Efficient Attention
Llms

[2602.21800] An Evaluation of Context Length Extrapolation in Long Code via Positional Embeddings and Efficient Attention

This paper evaluates methods for context length extrapolation in long code using positional embeddings and efficient attention mechanisms...

arXiv - AI · 3 min ·
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