ML applications

LLMs Can Now Solve Challenging Math Problems with Minimal Data: Researchers from UC Berkeley and Ai2 Unveil a Fine-Tuning Recipe That Unlocks Mathematical Reasoning Across Difficulty Levels

ML applications

5 Min Read

LLMs Can Now Solve Challenging Math Problems with Minimal Data: Researchers from UC Berkeley and Ai2 Unveil a Fine-Tuning Recipe That Unlocks Mathematical Reasoning Across Difficulty Levels

By Editorial Team

April 19, 2025

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IBM Releases Granite 3.3 8B: A New Speech-to-Text (STT) Model that Excels in Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST)

ML applications

4 Min Read

IBM Releases Granite 3.3 8B: A New Speech-to-Text (STT) Model that Excels in Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST)

By Editorial Team

April 18, 2025

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Do Reasoning Models Really Need Transformers?: Researchers from TogetherAI, Cornell, Geneva, and Princeton Introduce M1—A Hybrid Mamba-Based AI that Matches SOTA Performance at 3x Inference Speed

ML applications

4 Min Read

Do Reasoning Models Really Need Transformers?: Researchers from TogetherAI, Cornell, Geneva, and Princeton Introduce M1—A Hybrid Mamba-Based AI that Matches SOTA Performance at 3x Inference Speed

By Editorial Team

April 18, 2025

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LLM Reasoning Benchmarks are Statistically Fragile: New Study Shows Reinforcement Learning RL Gains often Fall within Random Variance

ML applications

5 Min Read

LLM Reasoning Benchmarks are Statistically Fragile: New Study Shows Reinforcement Learning RL Gains often Fall within Random Variance

By Editorial Team

April 17, 2025

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Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

ML applications

4 Min Read

Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

By Editorial Team

April 17, 2025

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From Logic to Confusion: MIT Researchers Show How Simple Prompt Tweaks Derail LLM Reasoning

ML applications

4 Min Read

From Logic to Confusion: MIT Researchers Show How Simple Prompt Tweaks Derail LLM Reasoning

By Editorial Team

April 17, 2025

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SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

ML applications

4 Min Read

SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

By Editorial Team

April 16, 2025

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MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

ML applications

4 Min Read

MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

By Editorial Team

April 16, 2025

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Transformers Can Now Predict Spreadsheet Cells without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets

ML applications

4 Min Read

Transformers Can Now Predict Spreadsheet Cells without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets

By Editorial Team

April 16, 2025

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SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

ML applications

5 Min Read

SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

By Editorial Team

April 15, 2025

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ML applications

LLMs Can Now Solve Challenging Math Problems with Minimal Data: Researchers from UC Berkeley and Ai2 Unveil a Fine-Tuning Recipe That Unlocks Mathematical Reasoning Across Difficulty Levels

IBM Releases Granite 3.3 8B: A New Speech-to-Text (STT) Model that Excels in Automatic Speech Recognition (ASR) and Automatic Speech Translation (AST)

Do Reasoning Models Really Need Transformers?: Researchers from TogetherAI, Cornell, Geneva, and Princeton Introduce M1—A Hybrid Mamba-Based AI that Matches SOTA Performance at 3x Inference Speed

LLM Reasoning Benchmarks are Statistically Fragile: New Study Shows Reinforcement Learning RL Gains often Fall within Random Variance

Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

From Logic to Confusion: MIT Researchers Show How Simple Prompt Tweaks Derail LLM Reasoning

SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

Transformers Can Now Predict Spreadsheet Cells without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets

SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

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