Science Question Answering
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Benchmarks
ScienceQA
Most implemented
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
Multimodal Chain-of-Thought Reasoning in Language Models
Towards CausalGPT: A Multi-Agent Approach for Faithful Knowledge Reasoning via Promoting Causal Consistency in LLMs
SciQAG: A Framework for Auto-Generated Science Question Answering Dataset with Fine-grained Evaluation
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
Honeybee: Locality-enhanced Projector for Multimodal LLM
Papers
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 Answering