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Natural Language Understanding

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하위 태스크: 2
평가표: 6
보존된 평가 기록: 42

Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.

Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/etsurin/summaug

공식 코드

Summarization-based Data Augmentation for Document Classification

https://github.com/explainableml/delora

공식 코드

DeLoRA: Decoupling Angles and Strength in Low-rank Adaptation

https://github.com/exploration-lab/scriptworld

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ScriptWorld: Text Based Environment For Learning Procedural Knowledge

https://github.com/facebookresearch/SentAugment

공식 코드

Self-training Improves Pre-training for Natural Language Understanding

https://github.com/facebookresearch/UNLU

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UnNatural Language Inference

https://github.com/facebookresearch/anli

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Adversarial NLI: A New Benchmark for Natural Language Understanding

https://github.com/facebookresearch/belebele

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The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants

https://github.com/facebookresearch/clutrr

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CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text

https://github.com/facebookresearch/craftassist

공식 코드

Why Build an Assistant in Minecraft?

https://github.com/facebookresearch/dst-egqa

공식 코드

Continual Dialogue State Tracking via Example-Guided Question Answering

https://github.com/facebookresearch/fairseq/tree/main/examples/data2vec

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Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language

https://github.com/facebookresearch/mmf/tree/main/projects/unit

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UniT: Multimodal Multitask Learning with a Unified Transformer

https://github.com/facebookresearch/multisense_consistency

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From Form(s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense Consistency

https://github.com/facico/goat-peft

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Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment

https://github.com/fangyihao/gptaug

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ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent Detection

https://github.com/fastnlp/cpt

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CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation

https://github.com/fatemafaria142/Large-Language-Models-Over-Transformer-Models-for-Bangla-NLI

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Unraveling the Dominance of Large Language Models Over Transformer Models for Bangla Natural Language Inference: A Comprehensive Study

https://github.com/faviq/faviq

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FaVIQ: FAct Verification from Information-seeking Questions

https://github.com/fdistinctions/ijcai18

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Empirical Analysis of Foundational Distinctions in Linked Open Data

https://github.com/fe1ixxu/intra-distillation

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The Importance of Being Parameters: An Intra-Distillation Method for Serious Gains

https://github.com/ffaisal93/dialect_copa

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Data-Augmentation-Based Dialectal Adaptation for LLMs

https://github.com/fhamborg/newstsc

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Towards Target-dependent Sentiment Classification in News Articles

https://github.com/fitz-like-coding/cwtm

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CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic Modeling

https://github.com/fkirste/gem_emnlp2022-toasts

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Analyzing Multi-Task Learning for Abstractive Text Summarization

https://github.com/frankaging/Causal-Distill

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Causal Distillation for Language Models

https://github.com/frankaging/Pragmatic-Color-Generation

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Pragmatically Informative Color Generation by Grounding Contextual Modifiers

https://github.com/freedomintelligence/acegpt

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AceGPT, Localizing Large Language Models in Arabic

https://github.com/fruttasecca/concept-tagging-with-neural-networks

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Concept Tagging for Natural Language Understanding: Two Decadelong Algorithm Development

https://github.com/garyyufei/promda

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PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks

https://github.com/gcunhase/StackedDeBERT

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Stacked DeBERT: All Attention in Incomplete Data for Text Classification

https://github.com/gingasan/sit3

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Code Summarization with Structure-induced Transformer

https://github.com/gladcolor/llm-geo

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Autonomous GIS: the next-generation AI-powered GIS

https://github.com/gmlwns2000/sea-attention

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SEA: Sparse Linear Attention with Estimated Attention Mask

https://github.com/gongqilinvu/a3c-rl

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Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning

https://github.com/google-research/bert

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/google-research/big_vision

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CLIPPO: Image-and-Language Understanding from Pixels Only

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