{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/train-probe","entry":"train_probe","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":6,"n_papers_ran":3,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":6,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":2,"ran_fixture":0,"ran":1,"unverified":3},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2604.12493","paper":"/paper/arxiv-2604-12493","title":"Latent Planning Emerges with Scale","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"hannamw/model-planning-public","path":"animal_stories/probing.py","file_url":"https://github.com/hannamw/model-planning-public/blob/HEAD/animal_stories/probing.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8674d9a18fef0cbd","mcp_get_code":{"code_sha256":"8674d9a18fef0cbd"}},{"arxiv_id":"2602.07812","paper":"/paper/arxiv-2602-07812","title":"LLMs Know More About Numbers than They Can Say","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"VCY019/Numeracy-Probing","path":"src/train_probe_arxiv.py","file_url":"https://github.com/VCY019/Numeracy-Probing/blob/HEAD/src/train_probe_arxiv.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7f2582833fce5e80","mcp_get_code":{"code_sha256":"7f2582833fce5e80"}},{"arxiv_id":"2602.02315","paper":"/paper/arxiv-2602-02315","title":"The Shape of Beliefs: Geometry, Dynamics, and Interventions along Representation Manifolds of Language Models' Posteriors","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"raphael-goodfire/shape-of-beliefs","path":"linear_field_probes.py","file_url":"https://github.com/raphael-goodfire/shape-of-beliefs/blob/HEAD/linear_field_probes.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"24829bb892bcde80","mcp_get_code":{"code_sha256":"24829bb892bcde80"}},{"arxiv_id":"2311.00863","paper":"/paper/training-dynamics-of-contextual-n-grams-in","title":"Training Dynamics of Contextual N-Grams in Language Models","date":"2023-11-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"luciaquirke/contextual-ngrams","path":"generate_checkpoint_probe_data.py","file_url":"https://github.com/luciaquirke/contextual-ngrams/blob/HEAD/generate_checkpoint_probe_data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"61f8653dac2da1f9","mcp_get_code":{"code_sha256":"61f8653dac2da1f9"}},{"arxiv_id":"2305.10204","paper":"/paper/shielded-representations-protecting-sensitive","title":"Shielded Representations: Protecting Sensitive Attributes Through Iterative Gradient-Based Projection","date":"2023-05-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"technion-cs-nlp/igbp_nonlinear-removal","path":"src/debias_representation.py","file_url":"https://github.com/technion-cs-nlp/igbp_nonlinear-removal/blob/HEAD/src/debias_representation.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a0117f0eefa663ec","mcp_get_code":{"code_sha256":"a0117f0eefa663ec"}},{"arxiv_id":"2024.findings-emnlp.918","paper":null,"title":"arXiv:2024.findings-emnlp.918","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"CLMBRs/targeted-xlms","path":"src/eval_probe.py","file_url":"https://github.com/CLMBRs/targeted-xlms/blob/HEAD/src/eval_probe.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2bc11e1614508b49","mcp_get_code":{"code_sha256":"2bc11e1614508b49"}}]}