Reposted by Sathvik
Accepted to Linguistic Inquiry!
I argue on syntactic grounds “some of the apples” is really “some apples of the apples” with NP-ellipsis. This explains which quantifiers and which modifiers (adjectives, prepositional phrases, relative clauses) can’t appear.
Preprint:
ling.auf.net/lingbuzz/009...
ling.auf.net
![Figure 1
Illustration of why AI systems cannot realistically scale to human cognition within the foreseeable future: (b) Human cognitive capacities (such as reasoning, communication, problem solving, learning, concept formation, planning etc.) can handle unbounded situations across many domains, ranging from simple to complex. (a) Engineers create AI systems using machine learning from human data. (d) In an attempt to approximate human cognition a lot of data is consumed. (c) Making AI systems that approximate human cognition is intractable (van Rooij, Guest, et al., 2024), i.e., the required resources (e.g. time, data) grows prohibitively fast as input domains get more complex, leading to diminishing returns. (a) Any existing AI system is
created in limited time (hours, months or years, not millennia or eons). Therefore, existing AI systems cannot realistically have the domain-general cognitive capacities that humans have. [Made with elements from freepik.com.]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:24ngrqljhck7hpvbgrg7a23k/bafkreie5dbxbxpaszqwfbgne6pi7kf26im6chq45olvzxyyrg7eitq6uue)
![from minicons import scorer
from nltk.tokenize import TweetTokenizer
lm = scorer.IncrementalLMScorer("gpt2")
# your own tokenizer function that returns a list of words
# given some sentence input
word_tokenizer = TweetTokenizer().tokenize
# word scoring
lm.word_score_tokenized(
["I was a matron in France", "I was a mat in France"],
bos_token=True, # needed for GPT-2/Pythia and NOT needed for others
tokenize_function=word_tokenizer,
bow_correction=True, # Oh and Schuler correction
surprisal=True,
base_two=True
)
'''
First word = -log_2 P(word | <beginning of text>)
[[('I', 6.1522440910339355),
('was', 4.033324718475342),
('a', 4.879510402679443),
('matron', 17.611848831176758),
('in', 2.5804288387298584),
('France', 9.036953926086426)],
[('I', 6.1522440910339355),
('was', 4.033324718475342),
('a', 4.879510402679443),
('mat', 19.385351181030273),
('in', 6.76780366897583),
('France', 10.574726104736328)]]
'''](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:njnapclhkbrhe3hsq44q2e4w/bafkreibw7fjs4zeocjmfvpr4fo7wikiqenbdz7b3clwq2rolckpoqwkssu)
