https://github.com/chenhaoxing/etl4video
공식 코드Efficient Transfer Learning for Video-language Foundation Models
Papers with Code 아카이브
General Knowledge
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 7
- 평가표
- 1
- 보존된 평가 기록
- 2
This task aims to evaluate the ability of a model to answer general-knowledge questions.
Source: BIG-bench
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/chenxin-dlut/seqtrackv2
공식 코드https://github.com/chunhualiu596/cswordassociation
공식 코드https://github.com/clovaai/attention-feature-distillation
공식 코드Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching
https://github.com/cmavro/gnn-rag
공식 코드GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
https://github.com/cmavro/tempoqr
공식 코드https://github.com/cogsys-tuebingen/Distilling-Stereo-Networks
공식 코드Distilling Stereo Networks for Performant and Efficient Leaner Networks
https://github.com/commonsense/conceptnet-numberbatch
공식 코드ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
https://github.com/craymichael/unfooling
공식 코드https://github.com/data-lang/text-summarization-sota-experiment
공식 코드Survey on Abstractive Text Summarization: Dataset, Models, and Metrics
https://github.com/datascienceuibk/hintqa
공식 코드Exploring Hint Generation Approaches in Open-Domain Question Answering
https://github.com/deepsportradar/camera-calibration-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/deepsportradar/instance-segmentation-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/deepsportradar/player-reidentification-challenge
공식 코드DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
https://github.com/delyan-boychev/imaginet
공식 코드ImagiNet: A Multi-Content Benchmark for Synthetic Image Detection
https://github.com/dojeon-ai/hare-tortoise
공식 코드Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks
https://github.com/dongxiangjue/closed-book-question-generation-via-contrastive-learning
공식 코드https://github.com/duygua/semeval2024_nli4ct
공식 코드D-NLP at SemEval-2024 Task 2: Evaluating Clinical Inference Capabilities of Large Language Models
https://github.com/edixiong/artificial-needles
공식 코드https://github.com/edward-sun/recite
공식 코드https://github.com/ellaneeman/disent_qa
공식 코드DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering
https://github.com/emorynlp/gpt-abceval
공식 코드Leveraging Large Language Models for Automated Dialogue Analysis
https://github.com/esteng/pragmatic_calibration
공식 코드LACIE: Listener-Aware Finetuning for Confidence Calibration in Large Language Models
https://github.com/ethanleo-lyx/llmqa
공식 코드Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering
https://github.com/eunseongc/mgfid
공식 코드https://github.com/event-ahu/medical_image_analysis
공식 코드Pre-training on High Definition X-ray Images: An Experimental Study
https://github.com/explainableml/general-knowledge-transfer
공식 코드https://github.com/facebookresearch/UnsupervisedQA
공식 코드https://github.com/facebookresearch/atlas
공식 코드Atlas: Few-shot Learning with Retrieval Augmented Language Models
https://github.com/facebookresearch/layerskip
공식 코드LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding
https://github.com/fanrena/dpt
공식 코드Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model
https://github.com/fantabulous-j/class
공식 코드Pre-training Cross-lingual Open Domain Question Answering with Large-scale Synthetic Supervision
https://github.com/fir-lat/hamos_ood
공식 코드Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection
https://github.com/fletcherjiang/llmepet
공식 코드Prior Knowledge Integration via LLM Encoding and Pseudo Event Regulation for Video Moment Retrieval
https://github.com/floatingstarZ/GeRSP
공식 코드Generic Knowledge Boosted Pre-training For Remote Sensing Images
https://github.com/fuzihaofzh/analyzeparameterefficientfinetune
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.