why aren't all 12 resolved? a statement only gets an assessment when the public
record can support or contradict it. opinions and what-ifs never can, and 0 checkable
ones are still open, waiting for their date. predictions held up or didn't;
assertions are supported or contradicted. on every card:
▮▮▮▮▮ certainty ·
▮▮▮▮▮ debate potential. speakers are clickable
Assertion Supported
Watkins: Over half of SWE-bench problems investigated by OpenAI had test flaws
“In over half of the problems that were investigated in that deep dive, there was one problem or the other. I think the most common problem are, like, overly narrow tests where there's some particular implementation detail that the tests were looking for but wa…”
Assertion Supported
Neubig: SWE-bench Scores Are Inflated By Training Data Contamination
“Sweebench is on popular open source repos and all of these popular open source repos were included in the training data for all of the language models. And so, the language models already know these repos. In some cases, the language models already know the in…”
Assertion Supported
SWE-Bench public test splits enable trivial cheating via runtime PR retrieval
“The entire test split here is public. So you can do things like just overfit to the patches in the test set. You can do things like, let me add at runtime, pull the PR and just get the answer and just use it.”
Assertion Supported
Pullen: CoScene's Genie outperforms OpenAI o1 out of the box on SWE-bench
“So it was obviously great to see, like, we still are better than O-one out of the box. You know, even with an older model, and I'm sure that that, that Delta will continue to grow once we're able to train O-one and once we've done more work on our dataset usin…”
Assertion Supported
Shawn Lewis: o1 agent achieves 57% single-pass, 64% with parallel rollouts
“It solves, like, something like 57% of problems with a single
Rollout and then using parallel rollouts and selecting the best one.
With other techniques, we get something like 64%.”
Assertion Supported
Yang: AI models falsely claim completion on impossible coding tasks
“I think they're all, the models are all kind of attempting and saying, like, oh, I did it, you know, so maybe not great.”
Assertion Supported
Cosine's fine-tuned GPT-4o scored higher on SWE-bench than OpenAI's original o1
“And then we also on this podcast, we interviewed Cosign that actually fine tune four O to, on three bench, sorry to achieve data on three bench. And that score was actually higher than O one when it came out.”
Assertion Supported
Augment Code open-sourced the SWE-bench implementation that reached number one
“We actually open sourced our implementation of Sweebench. So if you're curious how we got to number one, you'll be able to go see all the details of how we did it.”
Assertion Supported
Swyx: SWE-bench resolution rates surged from 13% to ~50% in 2024
“Keep in mind, we started the year at 13%. And so now we're about 50 open hands is around there.”
Assertion Supported
Hu: Honeycomb agent framework ranks number one on full SWE-bench dataset
“And then there's another one called Honeycomb, which also scored really well, and I think is number one on the full set.”
Assertion Supported
Hu: SWE-bench scores jumped from 3% on GPT-4 RAG to 43%
“If we just use GPT-IV plus RAG, what do we get? It's, like, a measly three percent. And then up to the most recent submissions where they get up to 43%.”
Assertion Supported
Cosine's SWE-bench model patch outputs are publicly verifiable on GitHub
“The patches are still public. So like the, dare I say, traditional Sweebench submission, you can go to a GitHub repo and see it and run them for yourself and verify that the numbers come out correctly.”