NLP Papers
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Generative Reward Models: Merging the Power of RLHF and RLAIF for Smarter AI
In this post we dive into a Stanford research presenting Generative Reward Models, a hybrid Human and AI RL to improve LLMs…
Introduction to Mixture-of-Experts | Original MoE Paper Explained
Diving into the original Google paper which introduced the Mixture-of-Experts (MoE) method, which was critical to AI progress…
Mixture-of-Agents Enhances Large Language Model Capabilities
In this post we explain the Mixture-of-Agents method, which shows a way to unite open-source LLMs to win GPT-4o on AlpacaEval 2.0…
Arithmetic Transformers with Abacus Positional Embeddings
In this post we dive into Abacus Embeddings, which dramatically enhance Transformers arithmetic capabilities with strong logical extrapolation…
CLLMs: Consistency Large Language Models
In this post we dive into Consistency Large Language Models (CLLMs), a new family of models which can dramatically speedup LLMs inference!…
ReFT: Representation Finetuning for Language Models
Learn about Representation Finetuning (ReFT) by Stanford University, a method to fine-tune large language models (LLMs) efficiently…
Stealing Part of a Production Language Model
What if we could discover OpenAI models internal weights? In this post we dive into a paper which presents an attack that steals LLMs data…
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
In this post we dive into the era of 1-bit LLMs paper by Microsoft, which shows a promising direction for low cost large language models…
Self-Rewarding Language Models by Meta AI
In this post we dive into the Self-Rewarding Language Models paper by Meta AI, which can possibly be a step towards open-source AGI…
Fast Inference of Mixture-of-Experts Language Models with Offloading
Diving into a research paper introducing an innovative method to enhance LLM inference efficiency using memory offloading…
LLM in a flash: Efficient Large Language Model Inference with Limited Memory
In this post we dive into LLM in a flash paper by Apple, that introduces a method to run LLMs on devices that have limited memory…
Orca 2: Teaching Small Language Models How to Reason
Dive into Orca 2 research paper, the second version of the successful Orca small language model from Microsoft…
CODEFUSION: A Pre-trained Diffusion Model for Code Generation
In this post we dive into Microsoft’s CODEFUSION, an approach to use diffusion models for code generation that achieves remarkable results…
Table-GPT: Empower LLMs To Understand Tables
In this post we dive into Table-GPT, a novel research by Microsoft, that empowers LLMs to understand tabular data…
Large Language Models As Optimizers – OPRO by Google DeepMind
In this post we dive into the Large Language Models As Optimizers paper by Google DeepMind, which introduces OPRO (Optimization by PROmpting)…
Code Llama Paper Explained
Discover an in-depth review of Code Llama paper, a specialized version of the Llama 2 model designed for coding tasks…
WizardMath – Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Diving into WizardMath, a LLM for mathematical reasoning contributed by Microsoft, surpassing models such as WizardLM and LLaMA-2…
Orca Research Paper Explained
In this post we dive into Orca’s paper which shows how to do imitation tuning effectively, outperforms ChatGPT with about 7% of its size!…