https://github.com/ffzzy840304/masked-pdpp
공식 코드Masked Diffusion with Task-awareness for Procedure Planning in Instructional Videos
Papers with Code 아카이브
Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/fhshubho/cgs-zsl
공식 코드https://github.com/fiction-zju/rulegpt
공식 코드HORAE: A Domain-Agnostic Language for Automated Service Regulation
https://github.com/fiorina1212/attention-buckets
공식 코드https://github.com/firenze11/finance_lm
공식 코드https://github.com/fireredteam/fireredasr
공식 코드https://github.com/fisht0ucher/trident
공식 코드https://github.com/fjq-tongji/mllm-sul
공식 코드https://github.com/flagopen/flagembedding
공식 코드Towards A Generalist Code Embedding Model Based On Massive Data Synthesis
https://github.com/flame-ruc/flame
공식 코드FLAME: Financial Large-Language Model Assessment and Metrics Evaluation
https://github.com/flavio2018/nesy23
공식 코드A Hybrid System for Systematic Generalization in Simple Arithmetic Problems
https://github.com/flexflow/flexflow
공식 코드https://github.com/flixpar/med-ts-llm
공식 코드MedTsLLM: Leveraging LLMs for Multimodal Medical Time Series Analysis
https://github.com/floridsleeves/llmdebugger
공식 코드Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step
https://github.com/floridsleeves/robustapi
공식 코드https://github.com/florin-git/Base-vs-Instruct-LLMs-in-RAG-Systems
공식 코드A Tale of Trust and Accuracy: Base vs. Instruct LLMs in RAG Systems
https://github.com/florin-git/The-Power-of-Noise
공식 코드https://github.com/flyfree5/lahore
공식 코드Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval
https://github.com/fminference/flexgen
공식 코드FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU
https://github.com/forestsking/chattime
공식 코드ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data
https://github.com/foundationvision/liquid
공식 코드https://github.com/fpcsong/BiLD
공식 코드BiLD: Bi-directional Logits Difference Loss for Large Language Model Distillation
https://github.com/fpezzuti/multistage-finetuning
공식 코드Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers
https://github.com/fploetzky/websci2024
공식 코드Lost in Recursion: Mining Rich Event Semantics in Knowledge Graphs
https://github.com/framartin/trap
공식 코드TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification
https://github.com/francesco-sovrano/from-philosophy-to-interfaces-an-explanatory-method-and-a-tool-inspired-by-achinstein-s-theory-of-e
공식 코드https://github.com/francesco-sovrano/yai4hu
공식 코드https://github.com/francescoferrini/multirelationalgnn
공식 코드Meta-Path Learning for Multi-relational Graph Neural Networks
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/francoisluus/KGReasoning
공식 코드https://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 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.