Alternatives and similar repositories for Awesome-LLM4Ranking

Users that are interested in Awesome-LLM4Ranking are comparing it to the libraries listed below

• gangiswag / llm-reranker
  ☆56Updated 11 months ago
• weizhepei / InstructRAG
  [ICLR 2025] InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
  ☆136Updated 11 months ago
• soyoung97 / ListT5
  official repository for ListT5
  ☆48Updated last month
• xlang-ai / BRIGHT
  [ICLR 2025] BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
  ☆184Updated 4 months ago
• castorini / perm-sc
  Official codebase for permutation self-consistency.
  ☆18Updated last year
• Hannibal046 / xRAG
  [Neurips2024] Source code for xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
  ☆167Updated last year
• liuqi6777 / pe_rank
  Leveraging passage embeddings for efficient listwise reranking with large language models.
  ☆49Updated last year
• THU-KEG / SeaKR
  ☆41Updated last year
• Alibaba-NLP / LaRA
  The code for LaRA Benchmark
  ☆46Updated 7 months 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"
  ☆82Updated last year
• facebookresearch / Multi-IF
  The evaluation code for MultiIF multi-turn and multi-lingual instruction following
  ☆59Updated last year
• dongguanting / DPA-RAG
  The code and data of DPA-RAG, accepted by WWW 2025 main conference.
  ☆63Updated 2 months ago
• orionw / FollowIR
  FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions
  ☆49Updated last year
• sean0042 / Open_WikiTable
  Open-WikiTable :Dataset for Open Domain Question Answering with Complex Reasoning over Table
  ☆27Updated 2 years ago
• texttron / BrowseComp-Plus
  BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent
  ☆154Updated last month
• orionw / rank1
  Test-time compute in information retrieval
  ☆49Updated 6 months ago
• shizhediao / Post-Training-Data-Flywheel
  We aim to provide the best references to search, select, and synthesize high-quality and large-quantity data for post-training your LLMs.
  ☆61Updated last year
• liuqi6777 / llm4ranking
  Large language models for document ranking.
  ☆71Updated this week
• kaistAI / Janus
  [NeurIPS 2024] Train LLMs with diverse system messages reflecting individualized preferences to generalize to unseen system messages
  ☆52Updated 5 months ago
• kaistAI / LangBridge
  [ACL 2024] LangBridge: Multilingual Reasoning Without Multilingual Supervision
  ☆95Updated last year
• facebookresearch / ReasonIR
  Official repository for paper "ReasonIR Training Retrievers for Reasoning Tasks".
  ☆213Updated 6 months ago
• RUC-NLPIR / CORAL
  CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation
  ☆65Updated 7 months ago
• OpenMatch / RAG-DDR
  [ICLR 2025] This is the code repo for our ICLR’25 paper "RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rew…
  ☆50Updated 11 months ago
• MozerWang / Loong
  [EMNLP 2024 (Oral)] Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA
  ☆145Updated 3 weeks ago
• gankim / tree-of-clarifications
  🌲 Code for our EMNLP 2023 paper - 🎄 "Tree of Clarifications: Answering Ambiguous Questions with Retrieval-Augmented Large Language Mode…
  ☆52Updated 2 years ago
• RUC-NLPIR / fullrank
  ☆39Updated 2 months ago
• carriex / recomp
  RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation.
  ☆144Updated last week
• 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
• OpenBMB / DEBATER
  This is the code repo for our paper "Learning More Effective Representations for Dense Retrieval through Deliberate Thinking Before Searc…
  ☆25Updated 10 months ago
• nlpai-lab / MIRAGE
  MIRAGE is a light benchmark to evaluate RAG performance.
  ☆33Updated 8 months ago