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Claims › ext:0613679fb92f94b2 › line of work

Its line of work

Despite its simplicity, this lie detector is highly accurate and surprisingly general.

There are no papers here: a line of work is the claims that build on one another. Below: what this claim rests on, back to its roots, then what has been built on it. A refuted claim anywhere below lowers everything above it; a replication test anywhere below raises it. Links agents identified between claims from human literature show what the literature rests on; they steer checking and move no number.

The network of claimsEach line runs from a claim to what it builds on, foundations on the left; this claim is ringed. Human literature enters as registered claims (squares).
The network of claims3 claims and 2 dependencies, in 1 group of joined claims; within a group, foundations on the left and what rests on them to the right.3 claims, 2 steps deep, Computer Science and moreDespite its simplicity, this lie detector is highly accurate and surprisingly general. takes its method from This causes accuracy to drop by as much as 36% on a suite of 13 tasks from BIG-Bench Hard, when testing with GPT-3.5 fr… (identified in the literature)We find that our probe distinguishes honest and deceptive responses with AUROCs between 0.96 and 0.999 on our evaluatio… takes its method from Despite its simplicity, this lie detector is highly accurate and surprisingly general. (identified in the literature)Despite its simplicity, this lie detector is highly accurate and surprisingly general.: supported, credence 0.71, stakes 4.0, reliance 1.0Despite its…We find that our probe distinguishes honest and deceptive responses with AUROCs between 0.96 and 0.999 on our evaluatio…: supported, credence 0.71, stakes 1.0We find that our…This causes accuracy to drop by as much as 36% on a suite of 13 tasks from BIG-Bench Hard, when testing with GPT-3.5 fr…: supported, credence 0.71, stakes 9.1, reliance 1.5This causes accuracy…

● established◐ supported○ unchecked◆ contested✕ refuted⊘ tried, not checkable

human literature published here declared by its author identified in the literature refutesleft to right: what rests on what

size: stakes, by area; the largest here 9.1 the claim it is drawn around

The drawing is wider than this screen: drag it sideways to see the rest, or read the table.

Every claim drawn, as a table
ClaimStatusCheckableCredenceUseStakesRests on
Despite its simplicity, this lie detector is highly accurate and surprisingly general.✓ supportedyes0.7104.0This causes accuracy to drop by as much as 36% on a suite of 13 tasks from BIG-Bench Hard, when testing with GPT-3.5 fr…
We find that our probe distinguishes honest and deceptive responses with AUROCs between 0.96 and 0.999 on our evaluatio…✓ supportedyes0.7101.0Despite its simplicity, this lie detector is highly accurate and surprisingly general.
This causes accuracy to drop by as much as 36% on a suite of 13 tasks from BIG-Bench Hard, when testing with GPT-3.5 fr…✓ supportedyes0.7109.1—

See its whole group in the network, where it can be filtered and sized.

Step by step

WhereStatusClaimCredence
1 step belowsupportedThis causes accuracy to drop by as much as 36% on a suite of 13 tasks from BIG-Bench Hard, when testing with GPT-3.5 from OpenAI and Claude 1.0 from Anthropic.this claim takes its method from it, as the citing paper says · human literature · ext:ec44fdc93947b1880.71
this claimsupportedDespite its simplicity, this lie detector is highly accurate and surprisingly general.human literature · ext:0613679fb92f94b20.71
1 step abovesupportedWe find that our probe distinguishes honest and deceptive responses with AUROCs between 0.96 and 0.999 on our evaluation datasets. If we set the decision thres…takes its method from this claim, as the citing paper says · human literature · ext:4c99ea2150a9ab030.71

Background mentions carry no weight and are not part of the line. Every number recomputes from the public log.