nelson-liu / lost-in-the-middle
Code and data for "Lost in the Middle: How Language Models Use Long Contexts"
☆334Updated last year
Alternatives and similar repositories for lost-in-the-middle:
Users that are interested in lost-in-the-middle are comparing it to the libraries listed below
- [EMNLP 2023] Adapting Language Models to Compress Long Contexts☆296Updated 6 months ago
- A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic…☆330Updated 10 months ago
- Official implementation for the paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"☆475Updated 2 months ago
- A large-scale, fine-grained, diverse preference dataset (and models).☆335Updated last year
- [ACL'24 Outstanding] Data and code for L-Eval, a comprehensive long context language models evaluation benchmark☆374Updated 8 months ago
- This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.☆451Updated last year
- ☆277Updated last year
- A Survey on Data Selection for Language Models☆218Updated 5 months ago
- DSIR large-scale data selection framework for language model training☆244Updated 11 months ago
- Implementation of paper Data Engineering for Scaling Language Models to 128K Context☆454Updated last year
- ☆253Updated last year
- This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.☆543Updated last year
- ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels …☆254Updated last year
- All available datasets for Instruction Tuning of Large Language Models☆247Updated last year
- Codes for the paper "∞Bench: Extending Long Context Evaluation Beyond 100K Tokens": https://arxiv.org/abs/2402.13718☆313Updated 5 months ago
- RewardBench: the first evaluation tool for reward models.☆526Updated 3 weeks ago
- [EMNLP 2023] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning☆236Updated last year
- Deita: Data-Efficient Instruction Tuning for Alignment [ICLR2024]☆542Updated 3 months ago
- [EMNLP 2023] Enabling Large Language Models to Generate Text with Citations. Paper: https://arxiv.org/abs/2305.14627☆478Updated 5 months ago
- A curated list of Human Preference Datasets for LLM fine-tuning, RLHF, and eval.☆349Updated last year
- Official repository for ORPO☆445Updated 9 months ago
- [ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning☆421Updated 5 months ago
- Pytorch implementation of DoReMi, a method for optimizing the data mixture weights in language modeling datasets☆316Updated last year
- Official repository of NEFTune: Noisy Embeddings Improves Instruction Finetuning☆393Updated 10 months ago
- ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings - NeurIPS 2023 (oral)☆261Updated 11 months ago
- [EMNLP 2024] LongAlign: A Recipe for Long Context Alignment of LLMs☆246Updated 3 months ago
- This is a collection of research papers for Self-Correcting Large Language Models with Automated Feedback.☆511Updated 4 months ago
- Generative Judge for Evaluating Alignment☆230Updated last year
- Learning to Compress Prompts with Gist Tokens - https://arxiv.org/abs/2304.08467☆281Updated last month
- Github repository for "RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models"☆160Updated 3 months ago