Reading Comprehension
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Benchmarks
ReClor
RACE
MuSeRC
AdversarialQA
CrowdSource QA
RadQA
ReCAM
Most implemented
Language Models are Few-Shot Learners
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Listen, Attend and Spell
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Bidirectional Attention Flow for Machine Comprehension
Language Models are Unsupervised Multitask Learners
Papers
Prompt2Skill: Unsupervised Skill Optimization From Natural Language Instructions
Skills are external artifacts that Large Language Models (LLMs) consume at inference time to improve their performance on specialized domains by incorporating relevant procedural and domain knowledge. Expert-authored ski…
Mathematical ReasoningReading ComprehensionQuestion AnsweringEnhancing Accessibility of Medical Texts through Large Language Model-Driven Plain Language Adaptation
This paper addresses the challenge of making complex healthcare information more accessible through automated Plain Language Adaptation (PLA). PLA aims to simplify technical medical language, bridging a critical gap betw…
Reading ComprehensionText SimplificationFew-Shot LearningLanguage Proficiency Assessment from Eye Movements in Naturalistic Passage Reading
Standard language proficiency tests rely on linguistic tasks such as vocabulary, grammar and reading comprehension quizzes. An alternative, cognitively motivated approach, introduced in Berzak et al. (2018), proposed ins…
Reading ComprehensionArkios: An Open Bilingual English-Nepali Language Model Trained From Scratch, with a Devanagari-Aware Tokenizer
We present Arkios, a 1.04B-parameter dense transformer pretrained from scratch on 150B tokens of bilingual English-Nepali text, using a custom single-file C/CUDA training stack and a Devanagari-aware byte-level BPE token…
Reading ComprehensionLEXIC: Lightweight Eye-tracking eXtension via Injected Complexity
On the recent EyeBench benchmark, predicting reading comprehension from eye movements exposes a stark gap: text-aware models using pretrained language models reach 56--63% AUROC, while gaze-only models operate at chance.…
Reading ComprehensionLLMs Struggle to Measure What Distinguishes Students of Different Proficiency Levels: A Study of Item Discrimination in Reading Comprehension Assessment
Item discrimination is a fundamental psychometric property of educational assessment, which measures whether an item meaningfully distinguishes students with higher proficiency from students with lower proficiency. While…
Reading Comprehension