Natural Language Inference

33개 벤치마크 · 논문 2,100편 · 이 태스크의 논문 보기 →

Benchmarks

Most implemented

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

2018-10-11 · 구현 534개

Language Models are Few-Shot Learners

2020-05-28 · 구현 67개

RoBERTa: A Robustly Optimized BERT Pretraining Approach

2019-07-26 · 구현 67개

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

2019-10-23 · 구현 57개

A Structured Self-attentive Sentence Embedding

2017-03-09 · 구현 52개

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

2019-09-26 · 구현 48개

Papers

A Comparative Explainability Framework for DeBERTa-v3 in Zero-Shot Medical Abstract Classification

2026-10-01 · Javier Diaz Esteban-Herreros, David Muñoz-Valero, Raquel Martínez-España, Jose M. Juarez 외 arxiv

A comparative explainability framework is presented to audit DeBERTa-v3 under zero-shot classification of medical abstracts. The work addresses the disagreement problem in Explainable Artificial Intelligence, where diffe…

Natural Language Inference Text Classification

An Empirical Study of Counterfactual Self-Explanations in LLMs

2026-09-15 · Giannis Kalyvas, Giorgos Filandrianos, Orfeas Menis Mastromichalakis, Vassilis Lyberatos 외 arxiv

Large language models can easily generate explanations for their own outputs, but such self-explanations are not necessarily faithful to the model's behavior. We study this issue through counterfactual self-explanations,…

Natural Language Inference Sentiment Analysis

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

2026-09-15 · Younes Boufouss, Luc Pommeret, Thomas Gerald, Patrick Paroubek 외 arxiv

While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable structures. This paper explores whether NLI can be performed using onl…

Natural Language Inference

Cascaded Batch Prompting

2026-08-27 · Sho Hoshino, Peinan Zhang arxiv

Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredictable downstream task performance. We propose cascaded batch prompting…

Natural Language Inference Question Answering

Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems

2026-08-21 · Balkrishna Giri, Md Toufique Hasan, Jussi Rasku, Muhammad Waseem 외 arxiv

Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they retrieve, creating a Security-Reliability Gap: high semantic relevance do…

Natural Language Inference

Structure, Association, and Decision Value: Representation-Based Difficulty Estimation for Adaptive Inference in African-Language NLI

2026-08-19 · Toheeb Ogunade arxiv

We ask whether internal representation statistics can provide useful example-level difficulty signals for adaptive inference in multilingual African NLP, and find that they cannot in this setting. Studying natural langua…

Natural Language Inference

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