Alternatives and similar repositories for SVAMP

Users that are interested in SVAMP are comparing it to the libraries listed below

• chaochun / nlu-asdiv-dataset
  ☆49Updated 2 years ago
• Shark-NLP / CoNT
  [NeurIPS'22 Spotlight] Data and code for our paper CoNT: Contrastive Neural Text Generation
  ☆153Updated 2 years ago
• sunlab-osu / Understanding-CoT
  ☆88Updated 2 years ago
• HKUNLP / icl-ceil
  [ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.
  ☆102Updated 2 years ago
• Alrope123 / rethinking-demonstrations
  ☆176Updated last year
• FranxYao / FlanT5-CoT-Specialization
  Implementation of ICML 23 Paper: Specializing Smaller Language Models towards Multi-Step Reasoning.
  ☆131Updated 2 years ago
• hkust-nlp / felm
  Github repository for "FELM: Benchmarking Factuality Evaluation of Large Language Models" (NeurIPS 2023)
  ☆59Updated last year
• FreedomIntelligence / ReasoningNLP
  paper list on reasoning in NLP
  ☆191Updated 5 months ago
• OhadRubin / EPR
  ☆63Updated 2 years ago
• KaiLv69 / UDR
  ACL'23: Unified Demonstration Retriever for In-Context Learning
  ☆38Updated last year
• nayeon7lee / FactualityPrompt
  ☆86Updated 2 years ago
• GXimingLu / neurologic_decoding
  ☆82Updated 2 years ago
• wenhuchen / Time-Sensitive-QA
  Code and Data for NeurIPS2021 Paper "A Dataset for Answering Time-Sensitive Questions"
  ☆73Updated 3 years ago
• yinzhangyue / SelfAware
  Do Large Language Models Know What They Don’t Know?
  ☆99Updated 10 months ago
• Yale-LILY / FeTaQA
  Dataset for TACL 2022 paper: "FeTaQA: Free-form Table Question Answering"
  ☆82Updated 2 years ago
• swj0419 / in-context-pretraining
  ☆53Updated last year
• princeton-nlp / MQuAKE
  [EMNLP 2023] MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
  ☆115Updated last year
• AlexTMallen / adaptive-retrieval
  ☆186Updated 2 months ago
• ellaneeman / disent_qa
  This code accompanies the paper DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering.
  ☆16Updated 2 years ago
• matt-seb-ho / WikiWhy
  WikiWhy is a new benchmark for evaluating LLMs' ability to explain between cause-effect relationships. It is a QA dataset containing 9000…
  ☆47Updated last year
• XiangLi1999 / ContrastiveDecoding
  contrastive decoding
  ☆203Updated 2 years ago
• eladsegal / strategyqa
  The official code of TACL 2021, "Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies".
  ☆78Updated 2 years ago
• OSU-NLP-Group / LLM-Knowledge-Conflict
  [ICLR'24 Spotlight] "Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts"
  ☆76Updated last year
• allanj / Deductive-MWP
  ☆63Updated 2 years ago
• GXimingLu / Quark
  ☆75Updated last year
• TianduoWang / MsAT
  [ACL 2023] Learning Multi-step Reasoning by Solving Arithmetic Tasks. https://arxiv.org/abs/2306.01707
  ☆24Updated 2 years ago
• xu1998hz / InstructScore_SEScore3
  First explanation metric (diagnostic report) for text generation evaluation
  ☆62Updated 6 months ago
• fanqiwan / Explore-Instruct
  EMNLP'2023: Explore-Instruct: Enhancing Domain-Specific Instruction Coverage through Active Exploration
  ☆36Updated last year
• Mayer123 / UDT-QA
  Code for the paper "Open Domain Question Answering with A Unified Knowledge Interface" (ACL 2022)
  ☆56Updated 2 years ago
• allenai / DecomP
  Repository for Decomposed Prompting
  ☆95Updated last year