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dial481

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[untitled]

1 points·by dial481·há 13 dias·0 comments

Show HN: Allelix – Annotate your DNA against 7 public databases offline

github.com
3 points·by dial481·há 28 dias·0 comments

[untitled]

1 points·by dial481·há 3 meses·0 comments

Show HN: Proposal for a real long-term AI memory benchmark

penfieldlabs.substack.com
4 points·by dial481·há 3 meses·0 comments

Milla Jovovich's MemPalace Claims 100% on LoCoMo. Its Benchmarks.md Disagrees

penfieldlabs.substack.com
4 points·by dial481·há 3 meses·0 comments

LoCoMo AI Benchmark: 6.4% of answer key wrong, judge accepts 63% of fake answers

github.com
3 points·by dial481·há 4 meses·3 comments

comments

dial481
·há 27 dias·discuss
This is badly needed. Jira is horrendous.

Can your plugin system support custom workflow triggers yet?
dial481
·há 28 dias·discuss
[flagged]
dial481
·há 28 dias·discuss
[flagged]
dial481
·há 3 meses·discuss
MemPalace's benchmark claims have been picked apart and debunked in the project's GitHub issues:

github.com/milla-jovovich/mempalace/issues/27 github.com/milla-jovovich/mempalace/issues/29 github.com/milla-jovovich/mempalace/issues/39 github.com/milla-jovovich/mempalace/issues/125 github.com/milla-jovovich/mempalace/issues/242

(and others)

TL;DR: When independent third parties ran actual end-to-end QA instead of retrieval metrics, the scores dropped dramatically.
dial481
·há 4 meses·discuss
That's encouraging to hear from someone with IR experience, thanks. Agree completely.
dial481
·há 4 meses·discuss
We audited the LoCoMo benchmark (one of the most cited eval for LLM agent memory) and found 99 score-corrupting errors in 1,540 questions (6.4%). Separately, we tested the LLM judge with adversarially generated wrong answers, it accepted 62.81% of vague-but-topical wrong answers. Some published system scores barely clear that bar. Full audit with methodology, all 99 errors documented, and reproducible scripts.