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Collections including paper arxiv:2309.05463

Microsoft Research Papers

#PapersToRead from Microsoft Research in the broad space of Generative AI, Multi-agent systems, responsible AI practices, LLM Ops, and language models

Visual In-Context Prompting

Paper • 2311.13601 • Published Nov 22, 2023 • 14
AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

Paper • 2308.08155 • Published Aug 16, 2023 • 2
LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models

Paper • 2303.02927 • Published Mar 6, 2023 • 3
The Impact of Large Language Models on Scientific Discovery: a Preliminary Study using GPT-4

Paper • 2311.07361 • Published Nov 13, 2023 • 11

Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 84
Restarting on CPU Upgrade

368

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Open Ko-LLM Leaderboard
Running

63

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OpenCompass LLM Leaderboard
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10.1k

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Open LLM Leaderboard

Track, rank and evaluate open LLMs and chatbots

Llemma: An Open Language Model For Mathematics

Paper • 2310.10631 • Published Oct 16, 2023 • 45
Mistral 7B

Paper • 2310.06825 • Published Oct 10, 2023 • 43
Qwen Technical Report

Paper • 2309.16609 • Published Sep 28, 2023 • 30
BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model

Paper • 2309.11568 • Published Sep 20, 2023 • 9

Dataset generation

Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs

Paper • 2310.13961 • Published Oct 21, 2023 • 4
ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Paper • 2202.07922 • Published Feb 16, 2022 • 1
Let's Synthesize Step by Step: Iterative Dataset Synthesis with Large Language Models by Extrapolating Errors from Small Models

Paper • 2310.13671 • Published Oct 20, 2023 • 17
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs

Paper • 2309.09582 • Published Sep 18, 2023 • 4

CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion

Paper • 2310.11248 • Published Oct 17, 2023 • 3
Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 84
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Paper • 2309.04564 • Published Sep 8, 2023 • 14
What's In My Big Data?

Paper • 2310.20707 • Published Oct 31, 2023 • 9

Code Evaluation

Collection of Papers on Code Evaluation (from code generation language models)

A Survey on Language Models for Code

Paper • 2311.07989 • Published Nov 14, 2023 • 21
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Paper • 2102.04664 • Published Feb 9, 2021 • 2
Evaluating Large Language Models Trained on Code

Paper • 2107.03374 • Published Jul 7, 2021 • 6
Out of the BLEU: how should we assess quality of the Code Generation models?

Paper • 2208.03133 • Published Aug 5, 2022 • 2

Research on LLM

When can transformers reason with abstract symbols?

Paper • 2310.09753 • Published Oct 15, 2023 • 2
In-Context Pretraining: Language Modeling Beyond Document Boundaries

Paper • 2310.10638 • Published Oct 16, 2023 • 26
Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model

Paper • 2310.09520 • Published Oct 14, 2023 • 10
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Paper • 2309.08532 • Published Sep 15, 2023 • 50

DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation

Paper • 2309.16653 • Published Sep 28, 2023 • 41
GAIA: a benchmark for General AI Assistants

Paper • 2311.12983 • Published Nov 21, 2023 • 174
Textbooks Are All You Need II: phi-1.5 technical report

Paper • 2309.05463 • Published Sep 11, 2023 • 84

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 36
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Paper • 2005.11401 • Published May 22, 2020 • 11
LoRA: Low-Rank Adaptation of Large Language Models

Paper • 2106.09685 • Published Jun 17, 2021 • 25
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Paper • 2205.14135 • Published May 27, 2022 • 8

Everything about LLM

The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"

Paper • 2309.12288 • Published Sep 21, 2023 • 3
Are Emergent Abilities in Large Language Models just In-Context Learning?

Paper • 2309.01809 • Published Sep 4, 2023 • 3
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Paper • 2309.04564 • Published Sep 8, 2023 • 14
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

Paper • 2309.09400 • Published Sep 17, 2023 • 77

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