https://github.com/shawnhuang497/medplib
공식 코드Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine
Papers with Code 아카이브
Question Answering
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- 평가표
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- 보존된 평가 기록
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Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
( Image credit: SQuAD )
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shawnkx/SCDE
공식 코드SCDE: Sentence Cloze Dataset with High Quality Distractors From Examinations
https://github.com/shayankiyani98/cp
공식 코드https://github.com/sheikhshafayat/benqa
공식 코드BEnQA: A Question Answering and Reasoning Benchmark for Bengali and English
https://github.com/shengyuzhang/DeVLBert
공식 코드DeVLBert: Learning Deconfounded Visio-Linguistic Representations
https://github.com/shenyedepisa/rscmqa
공식 코드Copy-Move Forgery Detection and Question Answering for Remote Sensing Image
https://github.com/shi-labs/vcoder
공식 코드VCoder: Versatile Vision Encoders for Multimodal Large Language Models
https://github.com/shidaizi/remud
공식 코드HAIBU-ReMUD: Reasoning Multimodal Ultrasound Dataset and Model Bridging to General Specific Domains
https://github.com/shihabrashid-ucr/normy
공식 코드NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question Answering
https://github.com/shijx12/TransferNet
공식 코드https://github.com/shijx12/kqapro_baselines
공식 코드https://github.com/shiluohe/referencetrustabledecoding
공식 코드Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models
https://github.com/shimisalant/CWR
공식 코드Contextualized Word Representations for Reading Comprehension
https://github.com/shin-ee-chen/SIFo
공식 코드https://github.com/shininglab/cat
공식 코드Counterfactual Adversarial Learning with Representation Interpolation
https://github.com/shinying/dest
공식 코드https://github.com/shishicode/agot
공식 코드Soft-Prompting with Graph-of-Thought for Multi-modal Representation Learning
https://github.com/shmsw25/DecompRC
공식 코드Multi-hop Reading Comprehension through Question Decomposition and Rescoring
https://github.com/shmsw25/qa-hard-em
공식 코드A Discrete Hard EM Approach for Weakly Supervised Question Answering
https://github.com/showlab/all-in-one
공식 코드https://github.com/showlab/clvqa
공식 코드Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task
https://github.com/showlab/demovlp
공식 코드Revitalize Region Feature for Democratizing Video-Language Pre-training of Retrieval
https://github.com/showlab/egovlp
공식 코드https://github.com/showlab/lova3
공식 코드LOVA3: Learning to Visual Question Answering, Asking and Assessment
https://github.com/showlab/mist
공식 코드MIST: Multi-modal Iterative Spatial-Temporal Transformer for Long-form Video Question Answering
https://github.com/showlab/movieseq
공식 코드https://github.com/shtoshni92/span-rep
공식 코드https://github.com/shtuplus/iccc_cvpr2024
공식 코드Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning
https://github.com/shubhamagarwal92/mmd
공식 코드A Knowledge-Grounded Multimodal Search-Based Conversational Agent
https://github.com/shuohangwang/Cross-Thought
공식 코드https://github.com/shuohangwang/SeqMatchSeq
공식 코드https://github.com/shuohangwang/mprc
공식 코드R$^3$: Reinforced Reader-Ranker for Open-Domain Question Answering
https://github.com/shuoli90/traq
공식 코드TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction
https://github.com/shushanarakelyan/modular_code_search
공식 코드https://github.com/shuvenduroy/multimodal
공식 코드Benchmarking Vision-Language Contrastive Methods for Medical Representation Learning
https://github.com/shuzi/insuranceQA
공식 코드Applying Deep Learning to Answer Selection: A Study and An Open Task
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.