Live data from Hacker News

Disagreement among frontier LLMs on real-world fact-checks

lenz.io

51–60 of 377 posts

Re: Disagreement among frontier LLMs on real-world fact-checks

#51
Don't forget people Goodhart's law will make this "benchmark" moot in weeks if not days. It will get integrated back into the fold, it will look "solved" but there will still be no reasoning, just more statistical technical correctness because light has be shown on a new "problem" to solve. It will then be clamored as great "progress" that will "change everything".

PS: yes, I might or might not have a degree in corporate strategy & PR.

Re: Disagreement among frontier LLMs on real-world fact-checks

#52

looking at the claims i would say 5 humans would disagree even more than the llms some of the claims where llms disagree: "On May 18, 2026, Ukraine carried out a drone attack on Moscow, Russia." "The slogan "Simon Go Back" was chanted in opposition to the Simon Commission in British India (1928–1930)." "Neptune Deep will start delivering natural gas in 2027." "A hotel villa in Kyrgyzstan displayed a sign stating 'n…

These "Facts" are interesting. "Neptune Deep will start delivering natural gas in 2027." for example is not a fact, its a prediction. "On May 18, 2026, Ukraine carried out a drone attack on Moscow, Russia." is less of a fact and more of a litmus test for which sources of information you trust.

Re: Disagreement among frontier LLMs on real-world fact-checks

#53
post #41

Earlier quoted context omitted.

Many of the rows in that spreadsheet reference "current events", which models aren't expected to do much better at than a human making an educated guess! They all have cutoff dates either last year or early this year and know nothing about what happened in "April 2026". This is doubly problematic because you evaluated earlier models like Gemini Pro 3 instead of 3.1, GPT 5.4 instead of 5.5, etc... Given that it's only…

Two of the models used have retrieval capabilities and have access to newer information through search. The other three are parametric.

Comparing models with search tools to models without - when there's no option for "I am unable to answer this question without access to search" - doesn't make sense to me.

Re: Disagreement among frontier LLMs on real-world fact-checks

#54
post #2

Author here. 67% (95% CI 64–70%) of 1,000 recent real user claims to a fact-checking platform had at least one of GPT-5.4, Claude Opus 4.7, Gemini 3 Pro, Gemini 3 Pro+Search, and Sonar Pro dissent from the panel majority — or no majority formed at all. Panel-level Krippendorff's α (ordinal) = 0.639, i.e. nontrivial but limited agreement. Quick context on what's in the writeup and what isn't: - What's measured: parsed…

I don't see it mentioned explicitly in the methods section but I assume you prompted each model only once for each question? Did you consider prompting n-times in blank states to see if the models even agree with themselves?

Would also be interesting to add a virtual model that is simply the majority of all models and see how much the individual models differ from the "consensus".

Do you plan to add some sources in the related work section of baseline numbers for human expert disagreement in fact checking tasks (I'm assuming such studies exist).

Re: Disagreement among frontier LLMs on real-world fact-checks

#55
post #2

Author here. 67% (95% CI 64–70%) of 1,000 recent real user claims to a fact-checking platform had at least one of GPT-5.4, Claude Opus 4.7, Gemini 3 Pro, Gemini 3 Pro+Search, and Sonar Pro dissent from the panel majority — or no majority formed at all. Panel-level Krippendorff's α (ordinal) = 0.639, i.e. nontrivial but limited agreement. Quick context on what's in the writeup and what isn't: - What's measured: parsed…

Nice work. Sonar who?

It's one of Perplexity's search-tools-using models.

https://docs.perplexity.ai/docs/agent-api/models

Re: Disagreement among frontier LLMs on real-world fact-checks

#56
post #41

Earlier quoted context omitted.

Many of the rows in that spreadsheet reference "current events", which models aren't expected to do much better at than a human making an educated guess! They all have cutoff dates either last year or early this year and know nothing about what happened in "April 2026". This is doubly problematic because you evaluated earlier models like Gemini Pro 3 instead of 3.1, GPT 5.4 instead of 5.5, etc... Given that it's only…

Two of the models used have retrieval capabilities and have access to newer information through search. The other three are parametric.

The title mention "fact-checks", but "fact checking" is a process in which facts are checked against sources, not one where you are given a random fact and have to tell if it's true or false from your own memory. That's what is normally called a quiz game. So a more honest title for this research would be "Models answer differently to quiz questions".

Re: Disagreement among frontier LLMs on real-world fact-checks

#57
post #11

Here's the prompt they used: Classify this claim as of : " " Output exactly one label: True, Mostly True, Misleading, or False. No explanations, no qualifiers. The claims look like this: https://lenz.io/research/llm-disagreement/data.csv I put that in Datasette Lite to make it easier to explore. Here's an example of a disagreement: https://lite.datasette.io/?csv=https%3A%2F%2Fstatic.simonwil... The claim was "All alm…

False vs misleading doesn't seem like a disagreement?

Yes, they are much closer verdicts. True and Mostly True are also close. Used Krippendorff's α (ordinal) to not penalize much closer disagreements. 21% of the claims have models that are on the polar opposite sides - at least one True, and at least one False.

Re: Disagreement among frontier LLMs on real-world fact-checks

#58
post #11

Here's the prompt they used: Classify this claim as of : " " Output exactly one label: True, Mostly True, Misleading, or False. No explanations, no qualifiers. The claims look like this: https://lenz.io/research/llm-disagreement/data.csv I put that in Datasette Lite to make it easier to explore. Here's an example of a disagreement: https://lite.datasette.io/?csv=https%3A%2F%2Fstatic.simonwil... The claim was "All alm…

[flagged]

Re: Disagreement among frontier LLMs on real-world fact-checks

#60

looking at the claims i would say 5 humans would disagree even more than the llms some of the claims where llms disagree: "On May 18, 2026, Ukraine carried out a drone attack on Moscow, Russia." "The slogan "Simon Go Back" was chanted in opposition to the Simon Commission in British India (1928–1930)." "Neptune Deep will start delivering natural gas in 2027." "A hotel villa in Kyrgyzstan displayed a sign stating 'n…

These "Facts" are interesting. "Neptune Deep will start delivering natural gas in 2027." for example is not a fact, its a prediction. "On May 18, 2026, Ukraine carried out a drone attack on Moscow, Russia." is less of a fact and more of a litmus test for which sources of information you trust.

Indeed. Real-world claims are somewhat messy. Some of the standard benchmarks, e.g. the questions in AVeriTeC, share similar characteristics.
Post reply on HN