Papers Reading Comprehension
“Reading Comprehension” 태그가 달린 논문 1,822편 · 필터 해제
Enhancing 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 ComprehensionModeling semantic association in self-paced reading with language model embeddings
Semantic association between a word and its context has been identified as an important component of reading comprehension, even when word predictability is accounted for. Recent research has highlighted the potential of…
Reading ComprehensionMemoryDocDataSet: A Benchmark for Joint Conversational Memory and Long Document Reasoning
AI systems increasingly need to combine two demanding capabilities: navigating multi-session conversation history and performing deep reading comprehension within long documents. Yet no existing benchmark evaluates both …
Reading ComprehensionParameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models
While continual pretraining~(CPT) is a practical way to extend large language models to new languages, naïve finetuning on targeted data erodes existing capabilities through catastrophic forgetting. Organizing training a…
Reading ComprehensionContinual PretrainingLanguage AcquisitionGeneral KnowledgeTeaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies
Grounded claim factuality checking is important for large language model (LLM) applications such as retrieval-augmented generation, as it helps users assess the correctness of generated outputs. Existing metrics using en…
Reading ComprehensionA Multi-Agent Framework for Feature-Constrained Difficulty Control in Reading Comprehension Item Generation
Recent studies in difficulty-controlled reading comprehension item generation have leveraged large language models (LLMs) to produce items by adjusting difficulty-related features. However, existing methods typically rel…
Reading ComprehensionK-Quantization and its Impact on Output Performance
Recent advancements in large language models (LLMs) have shown their remarkable capacities in many NLP tasks. However, their substantial size often presents challenges for deployment. This necessitates efficient techniqu…
Reading ComprehensionModel CompressionHallucination as an Anomaly: Dynamic Intervention via Probabilistic Circuits
One of the most critical challenges in Large Language Models is their tendency to hallucinate, i.e., produce factually incorrect responses. Existing approaches show promising results in terms of hallucination correction,…
Reading ComprehensionDisentangling Linguistic Relatedness from Task Alignment in Cross-Lingual Transfer
We study cross-lingual transfer by fine-tuning seven large language models (4B--671B parameters) on Arabic and evaluating zero-shot reading comprehension on Semitic languages and non-Semitic controls. Across dense and Mi…
Cross-Lingual TransferReading ComprehensionApplications of the Transformer Architecture in AI-Assisted English Reading Comprehension
This paper studies interpretable and fair artificial intelligence architectures for understanding English reading. Introduced transformer-based models, integrating advanced attention mechanisms and gradient-based feature…
Reading ComprehensionThe AI Skills Shift: Mapping Skill Obsolescence, Emergence, and Transition Pathways in the LLM Era
As Large Language Models reshape the global labor market, policymakers and workers need empirical data on which occupational skills may be most susceptible to automation. We present the Skill Automation Feasibility Index…
Reading ComprehensionAI Assistance Reduces Persistence and Hurts Independent Performance
People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks progress, and prioritizes the other person's growth over immediate resu…
Mathematical ReasoningReading ComprehensionDo Emotions in Prompts Matter? Effects of Emotional Framing on Large Language Models
Emotional tone is pervasive in human communication, yet its influence on large language model (LLM) behaviour remains unclear. Here, we examine how first-person emotional framing in user-side queries affect LLM performan…
Mathematical ReasoningReading ComprehensionQuestion AnsweringTailoring AI-Driven Reading Scaffolds to the Distinct Needs of Neurodiverse Learners
Neurodiverse learners often require reading supports, yet increasing scaffold richness can sometimes overload attention and working memory rather than improve comprehension. Grounded in the Construction-Integration model…
Reading ComprehensionRobust Multilingual Text-to-Pictogram Mapping for Scalable Reading Rehabilitation
Reading comprehension presents a significant challenge for children with Special Educational Needs and Disabilities (SEND), often requiring intensive one-on-one reading support. To assist therapists in scaling this suppo…
Reading ComprehensionSynthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG
Synthetic data augmentation helps language models learn new knowledge in data-constrained domains. However, naively scaling existing synthetic data methods by training on more synthetic tokens or using stronger generator…
Reading ComprehensionData Augmentation