Near human performance in question answering?

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The document discusses a neural network system that achieves near-human performance on the SQuAD question answering dataset. However, the document argues this result requires context: SQuAD involves span selection within a paragraph where the answer is guaranteed to exist, and questions can often be answered through superficial clues without complex reasoning. While the system scores 84% F1 and humans 91%, humans were incentivized to answer quickly and their performance is underestimated. The document concludes neural networks perform clever pattern matching rather than true intelligence or reasoning, and can be easily fooled by examples beyond their training.

Science

Near human performance
in question answering?
Yoav Goldberg
Bar Ilan University

Near Human Performance
on the SQUAD Dataset
• "Neural systems achieve near-human performance
on Question Answering".
• Not really, let's see why.

Restricted QA Setup
• Restricted to questions that can be answered by
span selection.
• Need to ﬁnd the answer in a given paragraph.
• The answer is guaranteed to be in the paragraph.
• Annotators see the paragraph when asking the
question, resulting in high lexical similarity
between question and answer.

Near Human Performance?
• Human performance: 91.2 F1. 
Current best system: 84.0 F1.
• Humans on MTurk. Who are instructed to answer 5
answers in 2 minutes. That's 16 cent per question.
• Humans are wrong mostly in span boundaries.
• Also, when doing max-vote between several
humans, human perf goes up substantially.

How hard is the dataset?
• Do the questions require complex reasoning, or
can they be "cheated" using superﬁcial clues?

The Rankie cycle is sometimes referred to as _________
words from questions some verb only NP in sent

______ have powers of ..... and veto .....
words from questionNoun Phrase

______ have powers of ..... and veto .....
words from questionNoun Phrase
all of this can be ignored...

... Shakespeare scholar _____
What Shakespeare scholar is ....?

hold
hold Noun Phrase
collection
collection

what is goal of criminal punishment
is goal of criminal punishment_____

all can be "cheated away" using
some smart template matching.

all can be "cheated away" using
some smart template matching.
and the template-matching systems
can be easily fooled by tailored examples
that don't fool humans
(Percy Liang, personal communication)

To Summarize
• DL methods gets near human performance on SQUAD but:
• Still 84 F1 vs. 91.2 F1.
• Restricted QA Setting (span selection, within paragraph,
answer always present, high lexical overlap).
• Compared to under-incentivized humans.
• (91.2 is a low estimate of human performance)
• Questions can be answered with "cheating".
• (84.0 is a high estimate of DL performance)

Take away
• Neural systems / RNNs / ConvNets do very clever
pattern matching. Not "intelligence", not
"reasoning".
• Not everything can be pattern-matched.
• Pattern matchers can be easily fooled.

We explore how well the intersection between our own everyday memories and those captured by our smartphones can be used for what we call autobiographical authentication—a challenge-response authentication system that queries users about day-to-day experiences. Through three studies—two on MTurk and one field study—we found that users are good, but make systematic errors at answering autobiographical questions. Using Bayesian modeling to account for these systematic response errors, we derived a formula for computing a confidence rating that the attempting authenticator is the user from a sequence of question-answer responses. We tested our formula against five simulated adversaries based on plausible real-life counterparts. Our simulations indicate that our model of autobiographical authentication generally performs well in assigning high confidence estimates to the user and low confidence estimates to impersonating adversaries.

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1. Near human performance in question answering? Yoav Goldberg Bar Ilan University

3. Near Human Performance on the SQUAD Dataset • "Neural systems achieve near-human performance on Question Answering". • Not really, let's see why.

4. Restricted QA Setup • Restricted to questions that can be answered by span selection. • Need to ﬁnd the answer in a given paragraph. • The answer is guaranteed to be in the paragraph. • Annotators see the paragraph when asking the question, resulting in high lexical similarity between question and answer.

5. Near Human Performance? • Human performance: 91.2 F1.  Current best system: 84.0 F1. • Humans on MTurk. Who are instructed to answer 5 answers in 2 minutes. That's 16 cent per question. • Humans are wrong mostly in span boundaries. • Also, when doing max-vote between several humans, human perf goes up substantially.

6. How hard is the dataset? • Do the questions require complex reasoning, or can they be "cheated" using superﬁcial clues?

8. The Rankie cycle is sometimes referred to as _________ words from questions some verb only NP in sent

9. ______ have powers of ..... and veto ..... words from questionNoun Phrase

10. ______ have powers of ..... and veto ..... words from questionNoun Phrase all of this can be ignored...

11. ... Shakespeare scholar _____ What Shakespeare scholar is ....?

12. hold hold Noun Phrase collection collection

13. what is goal of criminal punishment is goal of criminal punishment_____

14. all can be "cheated away" using some smart template matching.

15. all can be "cheated away" using some smart template matching. and the template-matching systems can be easily fooled by tailored examples that don't fool humans (Percy Liang, personal communication)

16. all can be "cheated away" using some smart template matching. and the template-matching systems can be easily fooled by tailored examples that don't fool humans (Percy Liang, personal communication)Update: paper by Jia and Liang demonstrates this: https://arxiv.org/abs/1707.07328

17. To Summarize • DL methods gets near human performance on SQUAD but: • Still 84 F1 vs. 91.2 F1. • Restricted QA Setting (span selection, within paragraph, answer always present, high lexical overlap). • Compared to under-incentivized humans. • (91.2 is a low estimate of human performance) • Questions can be answered with "cheating". • (84.0 is a high estimate of DL performance)

18. Take away • Neural systems / RNNs / ConvNets do very clever pattern matching. Not "intelligence", not "reasoning". • Not everything can be pattern-matched. • Pattern matchers can be easily fooled.

Near human performance in question answering?

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