Reasoning Models
3 items across 1 edition. First seen Sat 12 Sep, last seen Sat 12 Sep.
- Terence Tao published the declaration on his blog on 11 September; it is signed by 25 Fields Medallists and argues that "solving problems is only a tool and proxy for achieving the primary goal of conceptual understanding and insight".
- The signatories write that AI solutions are "announced in a rush, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others", and warn that without that step "AI-conceived ideas would never become fully alive and the crucial human transmission chain between mathematicians would be lost".
- TechCrunch reports that New York University mathematician Tristan Buckmaster alleged OpenAI pressed him to exclude an Anthropic collaborator from credit on a mathematics problem, and questioned whether OpenAI had drawn on earlier Codex work to produce its own proof.
- The full text of the declaration is hosted at mathandai.org, which blocked our fetcher, so the quotations above are taken from Tao's own post and TechCrunch. Neither source gives a count of signatories who are also AI-lab collaborators.
- The paper, posted to arXiv on 9 September 2026 and announced in the 11 September listing, reports that the system "scored 30 out of 42 points at IMO 2026, reaching the gold-medal threshold".
- The abstract states the pipeline "operates entirely in natural language, with no formal prover, external tools, or internet access", using three Nemotron 3 Ultra checkpoints — the general-availability model and two post-trained specialists — in "an iterative search that generates, verifies, and refines candidate proofs", with a separate high-compute stage selecting each submission.
- The authors say they release both post-trained checkpoints plus the training data, training and inference code, the submitted solutions, and "Nemotron-IMO-Bench, a new benchmark of 200 novel olympiad-level problems".
- The arXiv abstract page carries no affiliation block; Hugging Face lists the institution as NVIDIA. The IMO score is the authors' own report of their own submission and is not peer reviewed.
- The paper, posted to arXiv on 10 September 2026, describes "a training-free agentic pipeline that, given only a natural-language problem, produces an answer, expresses it as a Lean 4 statement, and constructs a machine-checked proof", and reports "100% accuracy across all evaluated olympiad benchmarks, including AIME 2025, AIME 2026, and HMMT February 2026".
- The abstract states that when paired with the open-weight K2-Horizon-7B reasoner "it solves all six IMO 2026 problems".
- The design puts a statement judge in front of the prover to check that the Lean formalisation preserves the original problem, and an error-attribution judge that routes failures either to mathematical re-derivation or to local Lean repair — the guard against a proof that is machine-checked but of the wrong statement.
- This is a preprint with no peer review, and the benchmark figures are the authors' own runs. The abstract does not report compute cost or the number of attempts per problem.