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Found 9 papers, 4 papers with code
Sentence-Level or Token-Level? A Comprehensive Study on Knowledge Distillation
To substantiate our hypothesis, we systematically analyze the performance of distillation methods by varying the model size of student models, the complexity of text, and the difficulty of decoding procedure.
mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning
In the fields of computer vision and natural language processing, multimodal chart question-answering, especially involving color, structure, and textless charts, poses significant challenges.
Rational Sensibility: LLM Enhanced Empathetic Response Generation Guided by Self-presentation Theory
Having the ability to empathize is crucial for accurately representing human behavior during conversations.
Unraveling Key Factors of Knowledge Distillation
Knowledge distillation, a technique for model compression and performance enhancement, has gained significant traction in Neural Machine Translation (NMT).
Human-computer Interaction for Brain-inspired Computing Based on Machine Learning And Deep Learning: A Review
Focusing on the application scenarios of decoding text and speech from brain signals in human-computer interaction, this paper presents a comprehensive review of the brain-inspired computing models based on machine learning (ML) and deep learning (DL), tracking their evolution, application value, challenges and potential research trends.
Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training
Remarkably, we show that even smaller base models, when equipped with our proposed approach, can achieve results comparable to those of larger models, illustrating the potential of our approach in harnessing the power of rationales for improved multimodal reasoning.
A Survey on Image-text Multimodal Models
Amidst the evolving landscape of artificial intelligence, the convergence of visual and textual information has surfaced as a crucial frontier, leading to the advent of image-text multimodal models.
Enhancing Human-like Multi-Modal Reasoning: A New Challenging Dataset and Comprehensive Framework
Multimodal reasoning is a critical component in the pursuit of artificial intelligence systems that exhibit human-like intelligence, especially when tackling complex tasks.
DialogPaint: A Dialog-based Image Editing Model
We introduce DialogPaint, a novel framework that bridges conversational interactions with image editing, enabling users to modify images through natural dialogue.
