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Question Answering

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하위 태스크: 19
평가표: 153
보존된 평가 기록: 1,781

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/ccychongyanchen/vqatherapycrowdsourcing

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VQA Therapy: Exploring Answer Differences by Visually Grounding Answers

https://github.com/cdancette/detect-shortcuts

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Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

https://github.com/cdancette/rubi.bootstrap.pytorch

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RUBi: Reducing Unimodal Biases in Visual Question Answering

https://github.com/cdhx/markqa

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MarkQA: A large scale KBQA dataset with numerical reasoning

https://github.com/cdhx/qdtqa

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Question Decomposition Tree for Answering Complex Questions over Knowledge Bases

https://github.com/ceezh/llovi

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A Simple LLM Framework for Long-Range Video Question-Answering

https://github.com/chacha-chen/explanations-human-studies

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Machine Explanations and Human Understanding

https://github.com/chadlzx/nsp_qa

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A Neural-Symbolic Approach to Natural Language Understanding

https://github.com/chahatraj/Vignette

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VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models

https://github.com/chaitanyamalaviya/pachinko

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What if you said that differently?: How Explanation Formats Affect Human Feedback Efficacy and User Perception

https://github.com/chaitanyamalaviya/rationale_formats

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What if you said that differently?: How Explanation Formats Affect Human Feedback Efficacy and User Perception

https://github.com/chancefocus/pixiu

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PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

https://github.com/chandar-lab/epik-eval

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EpiK-Eval: Evaluation for Language Models as Epistemic Models

https://github.com/chandlerguan/blockskim

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Block-Skim: Efficient Question Answering for Transformer

https://github.com/changlin31/BossNAS

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BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search

https://github.com/chanliang/conner

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Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators

https://github.com/chantalmp/rad-restruct

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Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting

https://github.com/chaoyi-wu/pmc-llama

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PMC-LLaMA: Towards Building Open-source Language Models for Medicine

https://github.com/chaoyi-wu/radfm

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Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

https://github.com/chat-3d/chat-3d-v2

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Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers

https://github.com/chathurangishyalika/smartpilot

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SmartPilot: A Multiagent CoPilot for Adaptive and Intelligent Manufacturing

https://github.com/chen-gx/seer

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SEER: Facilitating Structured Reasoning and Explanation via Reinforcement Learning

https://github.com/chen-judge/GeoQA

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GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

https://github.com/chen-zichen/xplainllm_dataset

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XplainLLM: A Knowledge-Augmented Dataset for Reliable Grounded Explanations in LLMs

https://github.com/chengtan9907/mc-cot

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Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training

https://github.com/chengw07/InfoTS

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Time Series Contrastive Learning with Information-Aware Augmentations

https://github.com/chengyuehuang511/frames-vqa

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FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering

https://github.com/chenlong164/peit

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Property Enhanced Instruction Tuning for Multi-task Molecule Generation with Large Language Models

https://github.com/chenmientan/malmen

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Massive Editing for Large Language Models via Meta Learning

https://github.com/chenqi008/LateralThinking

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Weak-eval-Strong: Evaluating and Eliciting Lateral Thinking of LLMs with Situation Puzzles

https://github.com/chenyiqun/mmoa-rag

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Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning

https://github.com/chenyu-jiang/megatron-lm

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DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines

https://github.com/chenyugao-cs/sma

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Structured Multimodal Attentions for TextVQA

https://github.com/chenzcv7/motor

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Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining

https://github.com/chenzhongwu20/rulerag_icl_ft

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RuleRAG: Rule-guided retrieval-augmented generation with language models for question answering

https://github.com/chiahsuan156/KaggleDBQA

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KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers

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