Alternatives and similar repositories for FactCHD

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

• oriyor / reasoning-on-cots
  Implementation of the paper: "Answering Questions by Meta-Reasoning over Multiple Chains of Thought"
  ☆96Updated last year
• TIGER-AI-Lab / MAmmoTH2
  Official code for "MAmmoTH2: Scaling Instructions from the Web" [NeurIPS 2024]
  ☆145Updated 8 months ago
• hyintell / awesome-refreshing-llms
  EMNLP'23 survey: a curation of awesome papers and resources on refreshing large language models (LLMs) without expensive retraining.
  ☆134Updated last year
• yueyu1030 / AttrPrompt
  [NeurIPS 2023] This is the code for the paper `Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias`.
  ☆150Updated last year
• zorazrw / filco
  [Preprint] Learning to Filter Context for Retrieval-Augmented Generaton
  ☆192Updated last year
• WadeYin9712 / Dynosaur
  Code and data for "Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation" (EMNLP 2023)
  ☆64Updated 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"
  ☆69Updated 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…
  ☆114Updated last year
• abhika-m / FAVA
  ☆72Updated last year
• Leezekun / Directional-Stimulus-Prompting
  [NeurIPS 2023] Codebase for the paper: "Guiding Large Language Models with Directional Stimulus Prompting"
  ☆111Updated 2 years ago
• FreedomIntelligence / ReasoningNLP
  paper list on reasoning in NLP
  ☆190Updated 3 months ago
• ConiferLM / Conifer
  Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language Models
  ☆88Updated last year
• xlang-ai / BRIGHT
  BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
  ☆149Updated last month
• lifan-yuan / CRAFT
  Code for ICLR 2024 paper "CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets"
  ☆57Updated last year
• princeton-nlp / LLMBar
  [ICLR 2024] Evaluating Large Language Models at Evaluating Instruction Following
  ☆127Updated last year
• veronica320 / Faithful-COT
  Code and data accompanying our paper on arXiv "Faithful Chain-of-Thought Reasoning".
  ☆161Updated last year
• i-Eval / FairEval
  ☆139Updated last year
• qhjqhj00 / WebBrain
  ☆68Updated 2 years ago
• oriyor / ret-robust
  Implementation of the paper: "Making Retrieval-Augmented Language Models Robust to Irrelevant Context"
  ☆69Updated 11 months ago
• HITsz-TMG / awesome-llm-attributions
  A Survey of Attributions for Large Language Models
  ☆205Updated 10 months ago
• WHGTyen / BIG-Bench-Mistake
  A dataset of LLM-generated chain-of-thought steps annotated with mistake location.
  ☆81Updated 11 months ago
• weizhepei / InstructRAG
  [ICLR 2025] InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
  ☆106Updated 5 months ago
• kaistAI / CoT-Collection
  [EMNLP 2023] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
  ☆244Updated last year
• Hannibal046 / SelfMemory
  [Neurips2023] Source code for Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory
  ☆60Updated 2 years ago
• HKUNLP / icl-ceil
  [ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.
  ☆102Updated 2 years ago
• wwxu21 / CUT
  Source code of "Reasons to Reject? Aligning Language Models with Judgments"
  ☆58Updated last year
• TIGER-AI-Lab / Program-of-Thoughts
  Data and Code for Program of Thoughts [TMLR 2023]
  ☆279Updated last year
• RuochenZhao / Verify-and-Edit
  A framework for editing the CoTs for better factuality
  ☆51Updated last year
• AlexTMallen / adaptive-retrieval
  ☆181Updated last week
• DAMO-NLP-SG / contrastive-cot
  Contrastive Chain-of-Thought Prompting
  ☆64Updated last year