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Natural Language Inference

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Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given a "premise".

Example:

Premise	Label	Hypothesis
A man inspects the uniform of a figure in some East Asian country.	contradiction	The man is sleeping.
An older and younger man smiling.	neutral	Two men are smiling and laughing at the cats playing on the floor.
A soccer game with multiple males playing.	entailment	Some men are playing a sport.

Approaches used for NLI include earlier symbolic and statistical approaches to more recent deep learning approaches. Benchmark datasets used for NLI include SNLI, MultiNLI, SciTail, among others. You can get hands-on practice on the SNLI task by following this d2l.ai chapter.

Further readings:

Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches

코드

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

https://github.com/thu-bpm/softmv

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Enhancing Cross-lingual Natural Language Inference by Soft Prompting with Multilingual Verbalizer

https://github.com/thu-keg/sqc-score

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Evaluating Generative Language Models in Information Extraction as Subjective Question Correction

https://github.com/thumlp/nli4ct

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THiFLY Research at SemEval-2023 Task 7: A Multi-granularity System for CTR-based Textual Entailment and Evidence Retrieval

https://github.com/thunlp/ERNIE

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ERNIE: Enhanced Language Representation with Informative Entities

https://github.com/thunlp/KernelGAT

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Fine-grained Fact Verification with Kernel Graph Attention Network

https://github.com/thunlp/PTR

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PTR: Prompt Tuning with Rules for Text Classification

https://github.com/thunlp/SememePSO-Attack

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Word-level Textual Adversarial Attacking as Combinatorial Optimization

https://github.com/thunlp/SememeRNN

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Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes

https://github.com/thunlp/fastfid

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FastFiD: Improve Inference Efficiency of Open Domain Question Answering via Sentence Selection

https://github.com/tianjunz/tempera

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TEMPERA: Test-Time Prompting via Reinforcement Learning

https://github.com/timdettmers/bitsandbytes

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LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

https://github.com/timoschick/pet

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Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference

https://github.com/tingofurro/summac

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SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization

https://github.com/tobischimanski/climretrieve

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ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures

https://github.com/tomervolk/hyper-pada

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Example-based Hypernetworks for Out-of-Distribution Generalization

https://github.com/tommccoy1/hans

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Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference

https://github.com/tomo-ut/temporalnli_dataset

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Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models

https://github.com/tosingithub/bipol

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Bipol: Multi-axes Evaluation of Bias with Explainability in Benchmark Datasets

https://github.com/tristanratz/scu-text-evaluation

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On the Role of Summary Content Units in Text Summarization Evaluation

https://github.com/tsinghua-dhy/ceg

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Citation-Enhanced Generation for LLM-based Chatbots

https://github.com/tttthomasssss/iwcs2019

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Temporal and Aspectual Entailment

https://github.com/tuhinjubcse/Figurative-NLI

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Figurative Language in Recognizing Textual Entailment

https://github.com/tuhinjubcse/model-in-the-loop-fig-lang

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FLUTE: Figurative Language Understanding through Textual Explanations

https://github.com/tuhinjubcse/visualmetaphors

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I Spy a Metaphor: Large Language Models and Diffusion Models Co-Create Visual Metaphors

https://github.com/tyliupku/gen-nli

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Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference

https://github.com/tyliupku/nli-debiasing-datasets

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An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference

https://github.com/ucinlp/autoprompt

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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

https://github.com/uclmr/adversarial-nli

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Adversarially Regularising Neural NLI Models to Integrate Logical Background Knowledge

https://github.com/uclmr/jack

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Jack the Reader - A Machine Reading Framework

https://github.com/ufal/nlgi_eval

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Evaluating Semantic Accuracy of Data-to-Text Generation with Natural Language Inference

https://github.com/uiucnlp/mumuqa

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MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding

https://github.com/ukplab/peerqa

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PeerQA: A Scientific Question Answering Dataset from Peer Reviews

https://github.com/umanlp/zusammenqa

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ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering System

https://github.com/unitn-sml/physician-medLLM-interaction

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Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain

https://github.com/unveiled-the-red-hat/SEE-Few

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SEE-Few: Seed, Expand and Entail for Few-shot Named Entity Recognition

https://github.com/utahnlp/consistency

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A Logic-Driven Framework for Consistency of Neural Models

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