2 citations · 3 across the 9 of their papers we have counts for
9 papers
Cascaded Batch Prompting
Sho Hoshino, Peinan Zhang
Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredictable downstream task performa…
Does Self-Consistency Improve the Recall of Encyclopedic Knowledge?
Sho Hoshino, Ukyo Honda, Peinan Zhang
While self-consistency is known to improve performance on symbolic reasoning, its effect on the recall of encyclopedic knowledge is unclear due to a lack of targeted evaluation gro…
Out-of-the-Box Conditional Text Embeddings from Large Language Models
Kosuke Yamada, Peinan Zhang
Conditional text embedding is a proposed representation that captures the shift in perspective on texts when conditioned on a specific aspect. Previous methods have relied on exten…
LCTG Bench: LLM Controlled Text Generation Benchmark
Kentaro Kurihara, Masato Mita, Peinan Zhang +3
The rise of large language models (LLMs) has led to more diverse and higher-quality machine-generated text. However, their high expressive power makes it difficult to control outpu…
FaithCAMERA: Construction of a Faithful Dataset for Ad Text Generation
Akihiko Kato, Masato Mita, Soichiro Murakami +3
In ad text generation (ATG), desirable ad text is both faithful and informative. That is, it should be faithful to the input document, while at the same time containing important i…
AdTEC: A Unified Benchmark for Evaluating Text Quality in Search Engine Advertising
Peinan Zhang, Yusuke Sakai, Masato Mita +2
With the increase in the fluency of ad texts automatically created by natural language generation technology, there is high demand to verify the quality of these creatives in a rea…
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding
Ukyo Honda, Tatsushi Oka, Peinan Zhang +1
Recent models for natural language understanding are inclined to exploit simple patterns in datasets, commonly known as shortcuts. These shortcuts hinge on spurious correlations be…
Cross-lingual Transfer or Machine Translation? On Data Augmentation for Monolingual Semantic Textual Similarity
Sho Hoshino, Akihiko Kato, Soichiro Murakami +1
Learning better sentence embeddings leads to improved performance for natural language understanding tasks including semantic textual similarity (STS) and natural language inferenc…
Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding
Yuu Jinnai, Ukyo Honda, Tetsuro Morimura +1
One of the most important challenges in text generation systems is to produce outputs that are not only correct but also diverse. Recently, Minimum Bayes-Risk (MBR) decoding has ga…