https://github.com/fpezzuti/multistage-finetuning
공식 코드Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers
Papers with Code 아카이브
Large Language Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/framartin/trap
공식 코드TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification
https://github.com/franciscoliu/MLLMU-Bench
공식 코드Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench
https://github.com/franciszchen/surgbox
공식 코드SurgBox: Agent-Driven Operating Room Sandbox with Surgery Copilot
https://github.com/franco-galante/rgb-model
공식 코드Information Retrieval in the Age of Generative AI: The RGB Model
https://github.com/francois-rd/accord
공식 코드$\texttt{ACCORD}$: Closing the Commonsense Measurability Gap
https://github.com/fraunhofer-iais/chunking-strategies
공식 코드Rethinking Chunk Size For Long-Document Retrieval: A Multi-Dataset Analysis
https://github.com/freedomintelligence/acegpt
공식 코드https://github.com/freedomintelligence/huatuo-26m
공식 코드https://github.com/freedomintelligence/huatuogpt
공식 코드https://github.com/freedomintelligence/llmzoo
공식 코드https://github.com/freedomintelligence/rag-instruct
공식 코드RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
https://github.com/freedomintelligence/sharegpt-4o-image
공식 코드ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation
https://github.com/frenzymath/REAL-Prover
공식 코드REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning
https://github.com/frontierlabs/mapdia
공식 코드Interpersonal Memory Matters: A New Task for Proactive Dialogue Utilizing Conversational History
https://github.com/fsoft-ai4code/xmainframe
공식 코드XMainframe: A Large Language Model for Mainframe Modernization
https://github.com/fu-dayuan/preact
공식 코드https://github.com/fudan-zvg/Brain3D
공식 코드https://github.com/fudandisc/disc-finllm
공식 코드DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
https://github.com/fudandisc/disc-lawllm
공식 코드DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services
https://github.com/fudandisc/piors
공식 코드https://github.com/fudandisc/socialagent
공식 코드https://github.com/fudanselab/agent4se-paper-list
공식 코드Large Language Model-Based Agents for Software Engineering: A Survey
https://github.com/funaudiollm/cosyvoice
공식 코드https://github.com/funaudiollm/inspiremusic
공식 코드https://github.com/furrutiav/nllf-emnlp-2023
공식 코드Deep Natural Language Feature Learning for Interpretable Prediction
https://github.com/fusion-jena/automatic-kg-creation-with-llm
공식 코드https://github.com/fusion-jena/information-retrieval-using-multiple-llm-and-rag
공식 코드https://github.com/futuredialchallenge/2024-rag
공식 코드The 2nd FutureDial Challenge: Dialog Systems with Retrieval Augmented Generation (FutureDial-RAG)
https://github.com/futureeeeee/cognibench
공식 코드https://github.com/futureeeeee/dynamic-rag
공식 코드https://github.com/futureeeeee/mba
공식 코드MBA-RAG: a Bandit Approach for Adaptive Retrieval-Augmented Generation through Question Complexity
https://github.com/fuyu-quant/iblm
공식 코드Inductive-bias Learning: Generating Code Models with Large Language Model
https://github.com/gabriellasky/claim_optimization
공식 코드https://github.com/gair-nlp/deepresearcher
공식 코드DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments
https://github.com/gair-nlp/openresearcher
공식 코드OpenResearcher: Unleashing AI for Accelerated Scientific Research
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.