Papers Science Question Answering
“Science Question Answering” 태그가 달린 논문 27편 · 필터 해제
Memory Augmentation Unlocks Efficient Chain-of-Thought Reasoning
Large language models often rely on Chain-of-Thought (CoT) reasoning to solve complex tasks, but verbose reasoning traces introduce substantial inference overhead. CoT compression shortens generation, yet aggressive comp…
Science Question AnsweringMathematical ReasoningReasoning Beyond Literal: Cross-style Multimodal Reasoning for Figurative Language Understanding
Vision-language models (VLMs) have demonstrated strong reasoning abilities in literal multimodal tasks such as visual mathematics and science question answering. However, figurative language, such as sarcasm, humor, and …
Science Question AnsweringMultimodal ReasoningFine-Tuning vs. RAG for Multi-Hop Question Answering with Novel Knowledge
Multi-hop question answering is widely used to evaluate the reasoning capabilities of large language models (LLMs), as it requires integrating multiple pieces of supporting knowledge to arrive at a correct answer. While …
Multi-hop Question AnsweringScience Question AnsweringContinual PretrainingCross Domain Evaluation of Multimodal Chain-of-Thought Reasoning of different datasets into the Amazon CoT Framework
While recent work has extended CoT to multimodal settings, achieving state-of-the-art results on science question answering benchmarks like ScienceQA, the generalizability of these approaches across diverse domains remai…
Science Question AnsweringDomain GeneralizationMultimodal ReasoningBioRAG: A RAG-LLM Framework for Biological Question Reasoning
The question-answering system for Life science research, which is characterized by the rapid pace of discovery, evolving insights, and complex interactions among knowledge entities, presents unique challenges in maintain…
Information RetrievalQuestion AnsweringRAGRetrieval+2SciQAG: A Framework for Auto-Generated Science Question Answering Dataset with Fine-grained Evaluation
We introduce SciQAG, a novel framework for automatically generating high-quality science question-answer pairs from a large corpus of scientific literature based on large language models (LLMs). SciQAG consists of a QA g…
Open-Ended Question AnsweringQuestion AnsweringScience Question AnsweringVideo-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
In light of recent advances in multimodal Large Language Models (LLMs), there is increasing attention to scaling them from image-text data to more informative real-world videos. Compared to static images, video poses uni…
Science Question AnsweringText-to-Video GenerationVideo GenerationVisual Question Answering+2Automated Answer Validation using Text Similarity
Automated answer validation can help improve learning outcomes by providing appropriate feedback to learners, and by making question answering systems and online learning solutions more widely available. There have been …
Information RetrievalMultiple-choiceQuestion AnsweringRetrieval+2Honeybee: Locality-enhanced Projector for Multimodal LLM
In Multimodal Large Language Models (MLLMs), a visual projector plays a crucial role in bridging pre-trained vision encoders with LLMs, enabling profound visual understanding while harnessing the LLMs' robust capabilitie…
MMEScience Question AnsweringBoosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training
Multimodal reasoning is a challenging task that requires models to reason across multiple modalities to answer questions. Existing approaches have made progress by incorporating language and visual modalities into a two-…
Multimodal ReasoningScience Question AnsweringVisual Question Answering (VQA)ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science
Large language models record impressive performance on many natural language processing tasks. However, their knowledge capacity is limited to the pretraining corpus. Retrieval augmentation offers an effective solution b…
Document ClassificationGraph Neural NetworkLanguage ModelingLanguage Modelling+3Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
Large language models have demonstrated impressive universal capabilities across a wide range of open-ended tasks and have extended their utility to encompass multimodal conversations. However, existing methods encounter…
Image-based Generative Performance BenchmarkingLanguage ModelingLanguage ModellingScience Question Answering+11A Survey on Interpretable Cross-modal Reasoning
In recent years, cross-modal reasoning (CMR), the process of understanding and reasoning across different modalities, has emerged as a pivotal area with applications spanning from multimedia analysis to healthcare diagno…
Cross-Modal RetrievalDecision MakingExplanation GenerationFactual Visual Question Answering+8Towards CausalGPT: A Multi-Agent Approach for Faithful Knowledge Reasoning via Promoting Causal Consistency in LLMs
Despite the progress of foundation models, knowledge-based reasoning remains a persistent challenge due to their limited capacity for knowledge recall and inference. Existing methods primarily focus on encouraging these …
counterfactualQuestion AnsweringScience Question AnsweringCheap and Quick: Efficient Vision-Language Instruction Tuning for Large Language Models
Recently, growing interest has been aroused in extending the multimodal capability of large language models (LLMs), e.g., vision-language (VL) learning, which is regarded as the next milestone of artificial general intel…
ChatbotNatural Language UnderstandingQuestion AnsweringScience Question AnsweringT-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question Answering
Large Language Models (LLMs) have recently demonstrated exceptional performance in various Natural Language Processing (NLP) tasks. They have also shown the ability to perform chain-of-thought (CoT) reasoning to solve co…
Language ModelingLanguage ModellingLarge Language ModelQuestion Answering+1Multimodal Chain-of-Thought Reasoning in Language Models
Large language models (LLMs) have shown impressive performance on complex reasoning by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains as the rationale to infer the answer. However, …
HallucinationLanguage ModellingScience Question AnsweringTwo is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering
We propose a simple refactoring of multi-choice question answering (MCQA) tasks as a series of binary classifications. The MCQA task is generally performed by scoring each (question, answer) pair normalized over all the …
Binary ClassificationQuestion AnsweringScience Question AnsweringSentence+1Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
When answering a question, humans utilize the information available across different modalities to synthesize a consistent and complete chain of thought (CoT). This process is normally a black box in the case of deep lea…
Multimodal Deep LearningMultimodal ReasoningMultiple-choiceOpen-Domain Question Answering+4Ranking Facts for Explaining Answers to Elementary Science Questions
In multiple-choice exams, students select one answer from among typically four choices and can explain why they made that particular choice. Students are good at understanding natural language questions and based on thei…
Interpretable Machine LearningLearning-To-RankMultiple-choiceQuestion Answering+3