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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/yuvalkirstain/lm-evaluation-harness

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A Few More Examples May Be Worth Billions of Parameters

https://github.com/yuweicao-uic/xltime

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XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction

https://github.com/yuweihao/reclor

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ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

https://github.com/yuwfan/HGN

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Hierarchical Graph Network for Multi-hop Question Answering

https://github.com/yuwvandy/kg-llm-mdqa

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Knowledge Graph Prompting for Multi-Document Question Answering

https://github.com/yuyangdu01/llm-cl-vqa

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LLM-Assisted Multi-Teacher Continual Learning for Visual Question Answering in Robotic Surgery

https://github.com/yuyangsunshine/bioprotocolbench

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BioProBench: Comprehensive Dataset and Benchmark in Biological Protocol Understanding and Reasoning

https://github.com/yuyanislearning/CTRL-PG

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Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference

https://github.com/yuzcccc/mfb

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Multi-modal Factorized Bilinear Pooling with Co-Attention Learning for Visual Question Answering

https://github.com/yuzcccc/vqa-mfb

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Beyond Bilinear: Generalized Multimodal Factorized High-order Pooling for Visual Question Answering

https://github.com/yuzhaouoe/sae-based-representation-engineering

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Steering Knowledge Selection Behaviours in LLMs via SAE-Based Representation Engineering

https://github.com/yuzhenmao/fairness-finetuning

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Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks

https://github.com/yxh-y/tablerag

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TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning

https://github.com/yxli2123/loftq

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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

https://github.com/yxuansu/magic

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Language Models Can See: Plugging Visual Controls in Text Generation

https://github.com/yxw-11/tablap

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Accurate and Regret-aware Numerical Problem Solver for Tabular Question Answering

https://github.com/yzhan238/CGExpan

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Empower Entity Set Expansion via Language Model Probing

https://github.com/yzhjessica/cdvqa

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Change Detection Meets Visual Question Answering

https://github.com/yzleroy/revive

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REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering

https://github.com/yzy-bupt/SVBench

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SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding

https://github.com/z1zs/mmneuron

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MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model

https://github.com/zaaachary/csqa-kepr

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KEPR: Knowledge Enhancement and Plausibility Ranking for Generative Commonsense Question Answering

https://github.com/zahraabbasiantaeb/simquac

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Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions

https://github.com/zaiwen/cropgpt

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ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources

https://github.com/zaynmi/seada-vqa

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Semantic Equivalent Adversarial Data Augmentation for Visual Question Answering

https://github.com/zchoi/vcrn

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Visual Commonsense-aware Representation Network for Video Captioning

https://github.com/zchuz/sigir-mhqa

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Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering

https://github.com/zd11024/NaviLLM

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Towards Learning a Generalist Model for Embodied Navigation

https://github.com/zechenli03/qlevr

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QLEVR: A Diagnostic Dataset for Quantificational Language and Elementary Visual Reasoning

https://github.com/zechenli03/sensorllm

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SensorLLM: Human-Intuitive Alignment of Multivariate Sensor Data with LLMs for Activity Recognition

https://github.com/zefang-liu/adamole

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AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts

https://github.com/zefang-liu/lm-evaluation-harness

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SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security

https://github.com/zengrh3/StructuralMemory

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On the Structural Memory of LLM Agents

https://github.com/zengxingchen/chartqa-mllm

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Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning

https://github.com/zengxyyu/PMI-TR

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A Framework for Inference Inspired by Human Memory Mechanisms

https://github.com/zeqing-wang/timecausality

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TimeCausality: Evaluating the Causal Ability in Time Dimension for Vision Language Models

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