Alternatives and similar repositories for Augmentation-Adapted-Retriever

Users that are interested in Augmentation-Adapted-Retriever are comparing it to the libraries listed below

• oriyor / ret-robust
  Implementation of the paper: "Making Retrieval-Augmented Language Models Robust to Irrelevant Context"
  ☆76Updated last year
• Hannibal046 / SelfMemory
  [Neurips2023] Source code for Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory
  ☆62Updated 2 years ago
• RUCAIBox / LLM-Knowledge-Boundary
  Implementation of "Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation"
  ☆82Updated 2 years ago
• c-box / KnowledgeLifecycle
  Paper list of "The Life Cycle of Knowledge in Big Language Models: A Survey"
  ☆59Updated 2 years ago
• pldlgb / nuggets
  ☆87Updated 2 years ago
• yinzhangyue / SelfAware
  Do Large Language Models Know What They Don’t Know?
  ☆102Updated last year
• THU-KEG / KoLA
  [ICLR24] The open-source repo of THU-KEG's KoLA benchmark.
  ☆52Updated 2 years ago
• Hannibal046 / xRAG
  [Neurips2024] Source code for xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
  ☆167Updated last year
• THUNLP-MT / SKR
  Self-Knowledge Guided Retrieval Augmentation for Large Language Models (EMNLP Findings 2023)
  ☆28Updated 2 years ago
• pillowsofwind / Knowledge-Conflicts-Survey
  [EMNLP 2024] The official GitHub repo for the survey paper "Knowledge Conflicts for LLMs: A Survey"
  ☆150Updated last year
• kongds / scaling_sentemb
  Scaling Sentence Embeddings with Large Language Models
  ☆109Updated last year
• ZitongYang / Synthetic_Continued_Pretraining
  Code implementation of synthetic continued pretraining
  ☆144Updated 11 months ago
• ACL2023-Retrieval-LM / ACL2023-Retrieval-LM.github.io
  https://acl2023-retrieval-lm.github.io/
  ☆157Updated 2 years ago
• florin-git / The-Power-of-Noise
  Code and data for "The Power of Noise: Redefining Retrieval for RAG Systems"
  ☆68Updated 5 months ago
• zjunlp / TRICE
  [NAACL 2024] Making Language Models Better Tool Learners with Execution Feedback
  ☆42Updated last year
• OSU-NLP-Group / LLM-Knowledge-Conflict
  [ICLR'24 Spotlight] "Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts"
  ☆79Updated last year
• shizhediao / R-Tuning
  [NAACL 2024 Outstanding Paper] Source code for the NAACL 2024 paper entitled "R-Tuning: Instructing Large Language Models to Say 'I Don't…
  ☆126Updated last year
• OpenMOSS / Say-I-Dont-Know
  [ICML'2024] Can AI Assistants Know What They Don't Know?
  ☆85Updated last year
• Spico197 / Humpback
  🐋 An unofficial implementation of Self-Alignment with Instruction Backtranslation.
  ☆138Updated 7 months ago
• OpenLMLab / LongWanjuan
  Towards Systematic Measurement for Long Text Quality
  ☆37Updated last year
• tianyi-lab / Superfiltering
  [ACL'24] Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning
  ☆184Updated 6 months ago
• hongbinye / Cognitive-Mirage-Hallucinations-in-LLMs
  Repository for the paper "Cognitive Mirage: A Review of Hallucinations in Large Language Models"
  ☆47Updated 2 years ago
• princeton-nlp / QuRating
  [ICML 2024] Selecting High-Quality Data for Training Language Models
  ☆197Updated 3 weeks ago
• Junjie-Ye / ToolEyes
  [COLING 2025] ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios
  ☆71Updated 7 months ago
• Shark-NLP / self-adaptive-ICL
  self-adaptive in-context learning
  ☆45Updated 2 years ago
• princeton-nlp / MQuAKE
  [EMNLP 2023] MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
  ☆118Updated last year
• JetRunner / SuperICL
  Code for "Small Models are Valuable Plug-ins for Large Language Models"
  ☆132Updated 2 years ago
• Alab-NII / 2wikimultihop
  ☆133Updated 2 years ago
• mayubo2333 / LLM-IE
  EMNLP'2023 (Findings): Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!
  ☆45Updated last year
• dki-lab / Pangu
  Code for reproducing the ACL'23 paper: Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments
  ☆78Updated 7 months ago