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Found 5 papers, 0 papers with code
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.
