LLMs Can Be Misled by Surprising Data: Google DeepMind Introduces New Techniques to Predict and Reduce Unintended Knowledge Contamination
Source: MarkTechPost Large language models (LLMs) are continually evolving by ingesting vast quantities of text data, enabling them...
Fourier Neural Operators Just Got a Turbo Boost: Researchers from UC Riverside Introduce TurboFNO, a Fully Fused FFT-GEMM-iFFT Kernel Achieving Up to 150% Speedup over PyTorch
Source: MarkTechPost Fourier Neural Operators (FNO) are powerful tools for learning partial differential equation solution operators, but lack...
Meta AI Introduces Collaborative Reasoner (Coral): An AI Framework Specifically Designed to Evaluate and Enhance Collaborative Reasoning Skills in LLMs
Source: MarkTechPost Rethinking the Problem of Collaboration in Language Models Large language models (LLMs) have demonstrated remarkable capabilities...
NVIDIA Introduces CLIMB: A Framework for Iterative Data Mixture Optimization in Language Model Pretraining
Source: MarkTechPost Challenges in Constructing Effective Pretraining Data Mixtures As large language models (LLMs) scale in size and...
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
Source: MarkTechPost Language models have made significant strides in tackling reasoning tasks, with even small-scale supervised fine-tuning (SFT)...
LLMs Can Now Learn to Try Again: Researchers from Menlo Introduce ReZero, a Reinforcement Learning Framework That Rewards Query Retrying to Improve Search-Based Reasoning in RAG Systems
Source: MarkTechPost The domain of LLMs has rapidly evolved to include tools that empower these models to integrate...
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)
Source: MarkTechPost As artificial intelligence continues to integrate into enterprise systems, the demand for models that combine flexibility,...
Making AI-generated code more accurate in any language
Source: MIT News – Artificial intelligence Programmers can now use large language models (LLMs) to generate computer code...
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
Source: MarkTechPost Effective reasoning is crucial for solving complex problems in fields such as mathematics and programming, and...
Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints
Source: MarkTechPost The Challenge of Data Selection in LLM Pretraining Developing large language models entails substantial computational investment,...