cross-encoder
There are 37 repositories under cross-encoder topic.
PrithivirajDamodaran/FlashRank
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
mickymultani/RAG-with-Cross-Encoder-Reranker
Testing speed and accuracy of RAG with, and without Cross Encoder Reranker.
svjack/Sbert-ChineseExample
Sentence-Transformers Information Retrieval example on Chinese
jordane95/dual-cross-encoder
Dual Cross Encoder for Dense Retrieval
ALucek/rag-reranking
An overview of popular reranking models and architectures for 2 stage RAG pipelines
dwyl/rag-elixir-doc
Livebook to run a Phoenix_LiveView documentation Retrieval-Augmented Generation (RAG) enhanced LLM
cambridgeltl/BLICEr
Improving Bilingual Lexicon Induction with Cross-Encoder Reranking (Findings of EMNLP 2022). Keywords: Bilingual Lexicon Induction, Word Translation, Cross-Lingual Word Embeddings.
jacobmarks/emoji_search
Semantically Search Emojis From the Command Line!
jacobmarks/emoji-search-plugin
Semantic Emoji Search Plugin for FiftyOne
Dhyanesh18/rag-enterprise-search
A genral RAG Search chatbot, with SoTA RAG techniques such as HyDE, Hybrid retrieval with BM25 + RRF and Cross encoder reranking. Evaluated on the BEIR scifact dataset and compared all the different pipelines i tried along the way
jd-coderepos/rag-reranker-QA
This repository hosts the code to launch a streamlit Q&A app that locally uses LLMs in a RAG-Reranker workflow
abdulvahapmutlu/research-agent
A hybrid Research Assistant that combines an exact Knowledge Graph (Neo4j) with a Retrieval‑Augmented Generation pipeline (FAISS + Cross‑Encoder + FLAN‑T5) behind a sleek Streamlit interface.
charanhu/reranker_with_query_expansion
This repository showcases a comprehensive approach to information retrieval, document re-ranking, and language model integration. It incorporates techniques such as document chunking, embedding projection, and automatic query expansion to enhance the effectiveness of information retrieval systems.
shreyansh26/Accelerating-Cross-Encoder-Inference
Leveraging torch.compile to accelerate cross-encoder inference
D1ffic00lt/ai-pastproof
PastProof AI – ML core for automated fact-checking: ingests raw text, finds evidence in a custom corpus, and returns only the false claims it can refute, together with supporting passages and (optionally) an LLM explanation.
dynamicanupam/Fashion_Recommendation_System_using_RAG_pipeline
A GenAI based search system that scans numerous fashion product descriptions to recommend suitable options based on user queries.
eslammohamedtolba/Financial-Insight-Engine
An AI analyst with a hybrid LLM architecture 🤖. Uses a fine-tuned Phi-3 Mini (3.8B) for local RAG answer generation & Gemini 1.5 Pro for query analysis of SEC filings (AAPL, MSFT, GOOG, AMZN, META).
Hungreeee/Reranker-Encoders
TinyBERT-based bi-encoder, cross-encoder, and poly-encoder trained on MS MACRO for passage re-ranking
mertafacan/end-to-end-pdf-rag-system
End-to-end PDF RAG: FastAPI + Streamlit UI, Qdrant, and RAG workflows powered by LangChain/LangGraph. Dockerized with caching, optional GPU, and Prometheus/Grafana/Loki.
ProjectDossier/ESSIR-2023-Legal-Tutorial
Official respository for Legal Tutorial in The 14th European Summer School on Information Retrieval
VedantKothari01/DocInsight
AI-powered document originality and plagiarism risk detection system combining semantic similarity (SBERT), stylometric analysis, and citation masking for explainable, multi-layered originality scoring.
adarsh-k27r/SalahKart
Collection of some of my works during my internship period at Salahkart for preview and educational purpose only.
ericphann/search-for-movie-plots
Baseline models for searching for movie plots from Wikipedia articles. Techniques include BM25 (lexical search), bi/cross-encoding (semantic search), and retrieval-augmented generation (RAG) using Mistal 7B through Fireworks.ai.
esnanta/ai-doquery-chatbot
Prototipe Document Q&A Bot yang dirancang untuk menyajikan informasi terkait regulasi.
LEANDERANTONY/HelpmateAI_RAG_QA_System
Retrieval-Augmented QA system for research documents/insurance policies using LangChain, ChromaDB, and OpenAI LLMs. Supports query reranking and few-shot prompting.
mcxraider/sph-timeline-project
Timeline Project
pranav-ap/library_rag
A RAG agent for local document retrieval and answer generation
RLAlpha49/AniSearch-Model
AniSearchModel leverages Sentence-BERT (SBERT) models to generate embeddings for synopses, enabling the calculation of semantic similarities between descriptions. This allows users to find the most similar anime or manga based on a given description.
Sibo-Ding/Steam-Game-Search-Engine
A Web App for Searching Steam Games
KhaledYaish0/rag-streamlit-app
Ask questions to your PDFs using AI (RAG + Streamlit). Upload any PDF and get smart answers — powered by semantic search and summarization.
LeoFu9487/ModelPulse
LLM News & Research Radar : Self-Improving RAG Engine
MohamedNassih/Evaluation-Pertinence-Juridique-ML
Évaluation de la pertinence (question ↔ article juridique) en français. Pipeline complet (prépa → modèles → soumission) avec CamemBERT en bi-encodeur calibré (MSE/Spearman), + variantes cross-encoder.
Pinsuda-K/rag-game-patch-th
Hybrid RAG for Thai ROV patch notes: normalize diffs → hybrid retrieve (BM25 + dense in Chroma, MMR, optional bge reranker) → citation-first answers via FastAPI with OpenAI/Ollama generators. | ระบบ RAG ภาษาไทยสำหรับแพตช์โน้ต ROV
sarabesh/Retrieval-Reranker
Set of notebooks used to experiment and learn about retreival and reranking strategies provided by qdrant over BEIR MS-Macros dataset.
Sarb-jot/system-prompt-research
🔍 Analyze system prompts in large language models to understand design principles and enhance AI application effectiveness.
ycz425/qa_retrieval
Exploration of retrieval methods on the HotpotQA corpus, combining dense retrieval and feature-based reranking. Achieved a mean nDCG@10 of 0.9416 using LambdaRank with features such as cross-encoder score, LLM score, BM25 score, and token-based statistics—surpassing dense retriever + cross-encoder baselines.