{"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/get-prompts","entry":"get_prompts","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":21,"n_papers_ran":12,"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":21,"n_samples_ran":12,"n_samples_fingerprinted":3,"n_places":22,"n_places_pointer_only":11,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":3,"ran_fixture":1,"ran":8,"unverified":9},"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":"2605.10195","paper":"/paper/arxiv-2605-10195","title":"Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"PKU-SEC-Lab/SPEX","path":"bfs_async.py","file_url":"https://github.com/PKU-SEC-Lab/SPEX/blob/HEAD/bfs_async.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7090bebf15a5cf44","mcp_get_code":{"code_sha256":"7090bebf15a5cf44"}},{"arxiv_id":"2602.06486","paper":"/paper/arxiv-2602-06486","title":"JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"smiling-world/JADE","path":"jade/checklist/prompts.py","file_url":"https://github.com/smiling-world/JADE/blob/HEAD/jade/checklist/prompts.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"f958d2e3b817cbb3","mcp_get_code":{"code_sha256":"f958d2e3b817cbb3"}},{"arxiv_id":"2601.08467","paper":"/paper/arxiv-2601-08467","title":"Zero-Shot Distracted Driver Detection via Vision Language Models with Double Decoupling","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"mtakamichi/ZVL-DDD","path":"src/prompts.py","file_url":"https://github.com/mtakamichi/ZVL-DDD/blob/HEAD/src/prompts.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"ba3eecb3855cd5b6","mcp_get_code":{"code_sha256":"ba3eecb3855cd5b6"}},{"arxiv_id":"2510.07364","paper":"/paper/arxiv-2510-07364","title":"Base Models Know How to Reason, Thinking Models Learn When","date":"2025-10-08","month_inferred_from_arxiv_id":null,"title_source":"syntology","repo":"cvenhoff/thinking-llms-interp","path":"generate-responses/generate_responses.py","file_url":"https://github.com/cvenhoff/thinking-llms-interp/blob/HEAD/generate-responses/generate_responses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"95c01671f957ac42","mcp_get_code":{"code_sha256":"95c01671f957ac42"}},{"arxiv_id":"2507.00814","paper":null,"title":"arXiv:2507.00814","date":null,"month_inferred_from_arxiv_id":"2025-07","title_source":null,"repo":"baltaci-r/MoralAgents","path":"src/prompts.py","file_url":"https://github.com/baltaci-r/MoralAgents/blob/HEAD/src/prompts.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"04691f8392a2c3d9","mcp_get_code":{"code_sha256":"04691f8392a2c3d9"}},{"arxiv_id":"2505.22939","paper":"/paper/generative-social-choice-the-next-generation","title":"Generative Social Choice: The Next Generation","date":"2025-05-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sara-fish/gen-soc-choice-next-gen","path":"PROSE/queries/prompts/gen_iter_prompts.py","file_url":"https://github.com/sara-fish/gen-soc-choice-next-gen/blob/HEAD/PROSE/queries/prompts/gen_iter_prompts.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7c4f83b40638cece","mcp_get_code":{"code_sha256":"7c4f83b40638cece"}},{"arxiv_id":"2411.06424","paper":"/paper/ablation-is-not-enough-to-emulate-dpo-how","title":"Beyond Toxic Neurons: A Mechanistic Analysis of DPO for Toxicity Reduction","date":"2024-11-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yushi-y/dpo-toxic-neurons","path":"evaluation/generate_funcs.py","file_url":"https://github.com/yushi-y/dpo-toxic-neurons/blob/HEAD/evaluation/generate_funcs.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d635938df605fbd3","mcp_get_code":{"code_sha256":"d635938df605fbd3"}},{"arxiv_id":"2410.15778","paper":"/paper/reducing-hallucinations-in-vision-language","title":"Reducing Hallucinations in Vision-Language Models via Latent Space Steering","date":"2024-10-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shengliu66/vti","path":"vti_utils/icv_utils.py","file_url":"https://github.com/shengliu66/vti/blob/HEAD/vti_utils/icv_utils.py","status":"ran_fixture","verification_level":1,"contract_check":"DEP_MISSING","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bab95a1590abaf99","mcp_get_code":{"code_sha256":"bab95a1590abaf99"}},{"arxiv_id":"2410.02992","paper":"/paper/guided-stream-of-search-learning-to-better","title":"Guided Stream of Search: Learning to Better Search with Language Models via Optimal Path Guidance","date":"2024-10-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"symoon11/guided-stream-of-search","path":"stream-of-search/src/sample.py","file_url":"https://github.com/symoon11/guided-stream-of-search/blob/HEAD/stream-of-search/src/sample.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6ee6c56846603d81","mcp_get_code":{"code_sha256":"6ee6c56846603d81"}},{"arxiv_id":"2409.08248","paper":"/paper/textboost-towards-one-shot-personalization-of","title":"TextBoost: Towards One-Shot Personalization of Text-to-Image Models via Fine-tuning Text Encoder","date":"2024-09-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nahyeonkaty/textboost","path":"src/textboost/evaluation/core.py","file_url":"https://github.com/nahyeonkaty/textboost/blob/HEAD/src/textboost/evaluation/core.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f2e38d770c4f705f","mcp_get_code":{"code_sha256":"f2e38d770c4f705f"}},{"arxiv_id":"2408.01337","paper":"/paper/2408-01337","title":"MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models","date":"2024-08-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mulab-mir/muchomusic","path":"prepare_prompts.py","file_url":"https://github.com/mulab-mir/muchomusic/blob/HEAD/prepare_prompts.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"70500451e582cfbc","mcp_get_code":{"code_sha256":"70500451e582cfbc"}},{"arxiv_id":"2407.13647","paper":"/paper/weak-to-strong-reasoning","title":"Weak-to-Strong Reasoning","date":"2024-07-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"gair-nlp/weak-to-strong-reasoning","path":"src/inference_olympic.py","file_url":"https://github.com/gair-nlp/weak-to-strong-reasoning/blob/HEAD/src/inference_olympic.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1e4965b788c0a240","mcp_get_code":{"code_sha256":"1e4965b788c0a240"}},{"arxiv_id":"2406.18406","paper":"/paper/ircan-mitigating-knowledge-conflicts-in-llm","title":"IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons","date":"2024-06-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"danshi777/ircan","path":"src/3_enhance_and_evaluate.py","file_url":"https://github.com/danshi777/ircan/blob/HEAD/src/3_enhance_and_evaluate.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e2d17a2e0e06f143","mcp_get_code":{"code_sha256":"e2d17a2e0e06f143"}},{"arxiv_id":"2406.17720","paper":"/paper/arboretum-a-large-multimodal-dataset-enabling","title":"BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity","date":"2024-06-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"baskargroup/Arboretum","path":"model_validation/metadata/classname_gpt_sentence.py","file_url":"https://github.com/baskargroup/Arboretum/blob/HEAD/model_validation/metadata/classname_gpt_sentence.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"51ff8836051fdfad","mcp_get_code":{"code_sha256":"51ff8836051fdfad"}},{"arxiv_id":"2406.09714","paper":"/paper/large-language-model-validity-via-enhanced","title":"Large language model validity via enhanced conformal prediction methods","date":"2024-06-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jjcherian/conformal-safety","path":"src/dataset.py","file_url":"https://github.com/jjcherian/conformal-safety/blob/HEAD/src/dataset.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"94a610d9319c1840","mcp_get_code":{"code_sha256":"94a610d9319c1840"}},{"arxiv_id":"2406.09072","paper":"/paper/living-in-the-moment-can-large-language","title":"Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?","date":"2024-06-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhaochen0110/cotempqa","path":"config.py","file_url":"https://github.com/zhaochen0110/cotempqa/blob/HEAD/config.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a04566d8526cd8fc","mcp_get_code":{"code_sha256":"a04566d8526cd8fc"}},{"arxiv_id":"2406.08587","paper":"/paper/cs-bench-a-comprehensive-benchmark-for-large","title":"CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery","date":"2024-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"csbench/csbench","path":"vllm-main/examples/csbench/gen_model_answer_en.py","file_url":"https://github.com/csbench/csbench/blob/HEAD/vllm-main/examples/csbench/gen_model_answer_en.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"91157e74ee7e68c5","mcp_get_code":{"code_sha256":"91157e74ee7e68c5"}},{"arxiv_id":"2403.03194","paper":"/paper/magid-an-automated-pipeline-for-generating","title":"MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets","date":"2024-03-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"amazon-science/MAGID","path":"src/multimodal_dataset/datasets/MMDialog/tools.py","file_url":"https://github.com/amazon-science/MAGID/blob/HEAD/src/multimodal_dataset/datasets/MMDialog/tools.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"6ac2145bebd8c2f5","mcp_get_code":{"code_sha256":"6ac2145bebd8c2f5"}},{"arxiv_id":"2403.03194","paper":"/paper/magid-an-automated-pipeline-for-generating","title":"MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets","date":"2024-03-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"amazon-science/MAGID","path":"src/multimodal_dataset/datasets/MMDD/tools.py","file_url":"https://github.com/amazon-science/MAGID/blob/HEAD/src/multimodal_dataset/datasets/MMDD/tools.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"50c4dee73b4909b4","mcp_get_code":{"code_sha256":"50c4dee73b4909b4"}},{"arxiv_id":"2401.01967","paper":"/paper/a-mechanistic-understanding-of-alignment","title":"A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity","date":"2024-01-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ajyl/dpo_toxic","path":"toxicity/eval_interventions/generate_funcs.py","file_url":"https://github.com/ajyl/dpo_toxic/blob/HEAD/toxicity/eval_interventions/generate_funcs.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d635938df605fbd3","mcp_get_code":{"code_sha256":"d635938df605fbd3"}},{"arxiv_id":"2310.01446","paper":"/paper/adaptive-solver-framework-for-dynamic","title":"Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning","date":"2023-10-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"john1226966735/adaptive-solver","path":"prompt.py","file_url":"https://github.com/john1226966735/adaptive-solver/blob/HEAD/prompt.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7c79771a8d17e4a8","mcp_get_code":{"code_sha256":"7c79771a8d17e4a8"}},{"arxiv_id":"2307.10159","paper":"/paper/fabric-personalizing-diffusion-models-with","title":"FABRIC: Personalizing Diffusion Models with Iterative Feedback","date":"2023-07-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sd-fabric/fabric","path":"fabric/evaluation/utils.py","file_url":"https://github.com/sd-fabric/fabric/blob/HEAD/fabric/evaluation/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6b18247105039e14","mcp_get_code":{"code_sha256":"6b18247105039e14"}}]}