SlowGuess/NAACL_2022_OCR huggingface dataset:
Prompt	Method	Generation
I wanted to buy a video game console.	beam search	I went to the store and looked at all the options. I decided to go with the PS4. I went home and waited for the PS4 to arrive. When the PS4 arrived, I was very excited.
beam search + A★esque	I went to the store and looked at all the options. I decided to go with the PS4 because it was the most expensive. When I got home, I plugged the PS4 into my TV. The PS4 turned on and I was happy.
My roommate is from Germany.	beam search	She moved to the United States when she was 16. She has been in the United States for 10 years now. She is a great roommate.
beam search + A★esque	He came to the United States when he was 10 years old. He had a hard time adjusting to American culture. One day, he decided to move back to Germany. He was very happy to be back in his homeland.
Oliver was nervous about his wedding.	beam search	He had never been to a wedding before. He decided to go to the rehearsal dinner. The rehearsal dinner went very well. Oliver had a great time at his wedding.
beam search + A★esque	He had never been married before and didn't know what to expect. When the day of the wedding came, he was very nervous. When he walked down the aisle, he knew it was going to be great. Oliver and his wife had a wonderful wedding.
My friends all love to go to the club to dance.	beam search	One day I decided to go with them. We went to the club and had a great time. We danced all night and had a great time. We decided to go back next week.
beam search + A★esque	One day, I decided to go with them. We went to the club and danced all night. When we got home, I told my friends about the fun we had. They all agreed that it was the best night of their lives.
Table 20: Example generations for unconstrained story generation using beam search with and without A\*esque.
Words	Method	Generation
waste water heat	CGMH	what waste is there, it seems now?
TSMH	where was the waste - water heater?
NEUROLOGIC	How much water is waste heat?
NEUROLOGIC*	Why do we waste so much water to heat our homes?
Naples plague killed	CGMH	when would she finally turn twenty - one?
TSMH	why was the plague epidemic in naples not in fact killed?
NEUROLOGIC	Who was killed in the plague in Naples?
NEUROLOGIC*	How many people are killed by the plague in Naples?
controversial aspect imperialism	CGMH	what war was ever fought after american imperialism collapsed?
TSMH	what are some controversial aspects of present - day american imperialism?
NEUROLOGIC	Whose imperialism is it, anyway?
NEUROLOGIC*	What is the most controversial aspect of imperialism?
engines efficient steam	CGMH	or were they the very first steam engines efficient enough for mass - production?
TSMH	why are steam engines so energy-efficient, just like fossil fuels?
NEUROLOGIC	Why do you think steam engines are so efficient?
NEUROLOGIC*	Why are steam engines so efficient?
Table 21: Example generations for constrained question generation with NEUROLOGIC and baselines, including CGMH (Miao et al., 2019), TSMH (Zhang et al., 2020) and NEUROLOGIC (Lu et al., 2021).
Dataset	train	dev.	test
COMMONGEN (Lin et al., 2020)	32,651	993	1,497
WMT2013/2017 IATE (Dinu et al., 2019)	-	581	414
E2ENLG (Dušek et al., 2018)	4,862	547	630
Interrogative question (Zhang et al., 2020)	-	-	300
RocStories (Mostafazadeh et al., 2016)	45,496	1,871	1,871
Table 22: Details of datasets in downstream tasks.