nelson-liu / lost-in-the-middleLinks
Code and data for "Lost in the Middle: How Language Models Use Long Contexts"
☆373Updated 2 years ago
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
Sorting:
- ☆294Updated 2 years ago
- [EMNLP 2023] Adapting Language Models to Compress Long Contexts☆323Updated last year
- This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.☆544Updated last year
- [EMNLP 2023] Enabling Large Language Models to Generate Text with Citations. Paper: https://arxiv.org/abs/2305.14627☆505Updated last year
- Official implementation for the paper "DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models"☆532Updated 11 months ago
- This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.☆551Updated last year
- [ACL'24 Outstanding] Data and code for L-Eval, a comprehensive long context language models evaluation benchmark☆390Updated last year
- A package to evaluate factuality of long-form generation. Original implementation of our EMNLP 2023 paper "FActScore: Fine-grained Atomic…☆414Updated 8 months ago
- Data and Code for Program of Thoughts [TMLR 2023]☆302Updated last year
- ☆188Updated 6 months ago
- DSIR large-scale data selection framework for language model training☆268Updated last year
- ToolQA, a new dataset to evaluate the capabilities of LLMs in answering challenging questions with external tools. It offers two levels …☆284Updated 2 years ago
- Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them☆541Updated last year
- A curated list of Human Preference Datasets for LLM fine-tuning, RLHF, and eval.☆384Updated 2 years ago
- Implementation of paper Data Engineering for Scaling Language Models to 128K Context☆482Updated last year
- A large-scale, fine-grained, diverse preference dataset (and models).☆359Updated 2 years ago
- Inference-Time Intervention: Eliciting Truthful Answers from a Language Model☆564Updated 11 months ago
- Deita: Data-Efficient Instruction Tuning for Alignment [ICLR2024]☆580Updated last year
- A Survey on Data Selection for Language Models☆254Updated 8 months ago
- This is a collection of research papers for Self-Correcting Large Language Models with Automated Feedback.☆562Updated last year
- Github repository for "RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models"☆215Updated last year
- [EMNLP 2023] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning☆253Updated 2 years ago
- RewardBench: the first evaluation tool for reward models.☆675Updated 7 months ago
- [ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning☆511Updated last year
- Codes for the paper "∞Bench: Extending Long Context Evaluation Beyond 100K Tokens": https://arxiv.org/abs/2402.13718☆368Updated last year
- Generative Judge for Evaluating Alignment☆248Updated last year
- Learning to Compress Prompts with Gist Tokens - https://arxiv.org/abs/2304.08467☆303Updated 10 months ago
- What's In My Big Data (WIMBD) - a toolkit for analyzing large text datasets☆225Updated last year
- ☆282Updated last year
- Source Code of Paper "GPTScore: Evaluate as You Desire"☆259Updated 2 years ago