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Found 7 papers, 0 papers with code
Modality Alignment between Deep Representations for Effective Video-and-Language Learning
Our method directly optimizes CKA to make an alignment between video and text embedding representations, hence it aids the cross-modality attention module to combine information over different modalities.
Are LLM-Judges Robust to Expressions of Uncertainty? Investigating the effect of Epistemic Markers on LLM-based Evaluation
In line with the principle of honesty, there has been a growing effort to train large language models (LLMs) to generate outputs containing epistemic markers.
SWITCH: Studying with Teacher for Knowledge Distillation of Large Language Models
To mitigate these challenges, we propose SWITCH (Studying WIth TeaCHer for Knowledge Distillation), a novel approach that strategically incorporates the teacher model during the student's sequence generation.
MP2D: An Automated Topic Shift Dialogue Generation Framework Leveraging Knowledge Graphs
Through quantitative and qualitative experiments, we demonstrate MP2D's efficacy in generating dialogue with natural topic shifts.
Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources
To address the data scarcity issue in Conversational question answering (ConvQA), a dialog inpainting method, which utilizes documents to generate ConvQA datasets, has been proposed.
PR-MCS: Perturbation Robust Metric for MultiLingual Image Captioning
Vulnerability to lexical perturbation is a critical weakness of automatic evaluation metrics for image captioning.
Developing High Quality Training Samples for Deep Learning Based Local Climate Zone Classification in Korea
Two out of three people will be living in urban areas by 2050, as projected by the United Nations, emphasizing the need for sustainable urban development and monitoring.
