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Found 5 papers, 3 papers with code
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
Diffusion models have exhibited remarkable capabilities in text-to-image generation.
Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training
Accordingly, permutation on the training data is considered as a potential solution, since this can make the model predict antecedent words or tokens.
Hint-enhanced In-Context Learning wakes Large Language Models up for knowledge-intensive tasks
In-context learning (ICL) ability has emerged with the increasing scale of large language models (LLMs), enabling them to learn input-label mappings from demonstrations and perform well on downstream tasks.
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Large Language Models (LLMs) excel in various tasks, but they rely on carefully crafted prompts that often demand substantial human effort.
MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction
Generative methods greatly promote aspect-based sentiment analysis via generating a sequence of sentiment elements in a specified format.
Ranked #1 on
Aspect-Based Sentiment Analysis (ABSA)
on ACOS
Aspect-Based Sentiment Analysis
Aspect Category Detection
+10
