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Found 6 papers, 5 papers with code
Learning to Generate Explanation from e-Hospital Services for Medical Suggestion
Explaining the reasoning of neural models has attracted attention in recent years.
Measuring Taiwanese Mandarin Language Understanding
We present TMLU, a holistic evaluation suit tailored for assessing the advanced knowledge and reasoning capability in LLMs, under the context of Taiwanese Mandarin.
Fidelity-Enriched Contrastive Search: Reconciling the Faithfulness-Diversity Trade-Off in Text Generation
In this paper, we address the hallucination problem commonly found in natural language generation tasks.
Large Language Models Perform Diagnostic Reasoning
We explore the extension of chain-of-thought (CoT) prompting to medical reasoning for the task of automatic diagnosis.
Self-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations
Finally, we perform ICL for the test input with the pseudo-input-label pairs as demonstrations.
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models
Inspired by the implicit mental process of how human beings assess explanations, we present a novel approach, Zero-shot Augmentation of Rationale-Answer pairs (ZARA), to automatically construct pseudo-parallel data for self-training by reducing the problem of plausibility judgement to natural language inference.
