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Machine Learning

A branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

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# 🌳 Dive into Decision Trees: A Fun Guide! 🌳

# 🌳 Dive into Decision Trees: A Fun Guide! 🌳

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CRISP-DM: The Essential Methodology for Structuring Your Data Science Projects

CRISP-DM: The Essential Methodology for Structuring Your Data Science Projects

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4 min read
{sigma}-GPTs: A New Approach to Autoregressive Models

{sigma}-GPTs: A New Approach to Autoregressive Models

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3 min read
Bayesian Regression Markets

Bayesian Regression Markets

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Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text

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If in a Crowdsourced Data Annotation Pipeline, a GPT-4

If in a Crowdsourced Data Annotation Pipeline, a GPT-4

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Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion

Ctrl-V: Higher Fidelity Video Generation with Bounding-Box Controlled Object Motion

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My Experience with Python for Data Analysis

My Experience with Python for Data Analysis

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Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre

Cutting through buggy adversarial example defenses: fixing 1 line of code breaks Sabre

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4 min read
Repairing Catastrophic-Neglect in Text-to-Image Diffusion Models via Attention-Guided Feature Enhancement

Repairing Catastrophic-Neglect in Text-to-Image Diffusion Models via Attention-Guided Feature Enhancement

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4 min read
Bytes Are All You Need: Transformers Operating Directly On File Bytes

Bytes Are All You Need: Transformers Operating Directly On File Bytes

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Guide to Building Credit Risk Models with Machine Learning

Guide to Building Credit Risk Models with Machine Learning

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3 min read
Big Brother or Big Benefits? The Impact of Face Recognition on Our Lives

Big Brother or Big Benefits? The Impact of Face Recognition on Our Lives

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Day 9 of Machine Learning|| Linear Regression implementation

Day 9 of Machine Learning|| Linear Regression implementation

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Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics

Do LLMs Have Distinct and Consistent Personality? TRAIT: Personality Testset designed for LLMs with Psychometrics

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3 min read
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

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5 min read
Evaluating the Social Impact of Generative AI Systems in Systems and Society

Evaluating the Social Impact of Generative AI Systems in Systems and Society

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5 min read
ReFT: Reasoning with Reinforced Fine-Tuning

ReFT: Reasoning with Reinforced Fine-Tuning

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MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution

MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution

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Assessing the nature of large language models: A caution against anthropocentrism

Assessing the nature of large language models: A caution against anthropocentrism

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4 min read
The Remarkable Robustness of LLMs: Stages of Inference?

The Remarkable Robustness of LLMs: Stages of Inference?

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From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

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SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models

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5 min read
Thermometer: Towards Universal Calibration for Large Language Models

Thermometer: Towards Universal Calibration for Large Language Models

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4 min read
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data

From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data

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5 min read
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