{"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/laplace-smoothing","entry":"laplace_smoothing","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":8,"n_papers_ran":8,"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":4,"n_samples_ran":4,"n_samples_fingerprinted":1,"n_places":8,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":2,"ran_draft_wrong":1,"ran_fixture":0,"ran":1,"unverified":0},"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":"2604.22225","paper":"/paper/arxiv-2604-22225","title":"TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"xiaomi-research/tts-prism","path":"models/mimo_audio_tokenizer/quantization.py","file_url":"https://github.com/xiaomi-research/tts-prism/blob/HEAD/models/mimo_audio_tokenizer/quantization.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c360b5ccff704a88","mcp_get_code":{"code_sha256":"c360b5ccff704a88"}},{"arxiv_id":"2411.06070","paper":"/paper/gft-graph-foundation-model-with-transferable","title":"GFT: Graph Foundation Model with Transferable Tree Vocabulary","date":"2024-11-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zehong-wang/gft","path":"GFT/model/vq.py","file_url":"https://github.com/zehong-wang/gft/blob/HEAD/GFT/model/vq.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"702d64c397294ae2","mcp_get_code":{"code_sha256":"702d64c397294ae2"}},{"arxiv_id":"2407.05361","paper":"/paper/emilia-an-extensive-multilingual-and-diverse","title":"Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation","date":"2024-07-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"open-mmlab/Amphion","path":"models/codec/amphion_codec/quantize/vector_quantize.py","file_url":"https://github.com/open-mmlab/Amphion/blob/HEAD/models/codec/amphion_codec/quantize/vector_quantize.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b5240484210b398a","mcp_get_code":{"code_sha256":"b5240484210b398a"}},{"arxiv_id":"2401.06654","paper":"/paper/decoupling-pixel-flipping-and-occlusion","title":"Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks","date":"2024-01-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bluecher31/pixel-flipping","path":"conditional_explainer/helper_base.py","file_url":"https://github.com/bluecher31/pixel-flipping/blob/HEAD/conditional_explainer/helper_base.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"LGPL-2.1","inline_ok":false,"code_sha256_prefix":"5d6f5c141b36c5f5","mcp_get_code":{"code_sha256":"5d6f5c141b36c5f5"}},{"arxiv_id":"2401.01885","paper":"/paper/from-audio-to-photoreal-embodiment","title":"From Audio to Photoreal Embodiment: Synthesizing Humans in Conversations","date":"2024-01-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/audio2photoreal","path":"model/vqvae.py","file_url":"https://github.com/facebookresearch/audio2photoreal/blob/HEAD/model/vqvae.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c360b5ccff704a88","mcp_get_code":{"code_sha256":"c360b5ccff704a88"}},{"arxiv_id":"2308.16692","paper":"/paper/speechtokenizer-unified-speech-tokenizer-for","title":"SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models","date":"2023-08-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ZhangXInFD/SpeechTokenizer","path":"speechtokenizer/quantization/core_vq.py","file_url":"https://github.com/ZhangXInFD/SpeechTokenizer/blob/HEAD/speechtokenizer/quantization/core_vq.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c360b5ccff704a88","mcp_get_code":{"code_sha256":"c360b5ccff704a88"}},{"arxiv_id":"2308.02117","paper":"/paper/vqgraph-graph-vector-quantization-for","title":"VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs","date":"2023-08-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yangling0818/vqgraph","path":"vq.py","file_url":"https://github.com/yangling0818/vqgraph/blob/HEAD/vq.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"b5240484210b398a","mcp_get_code":{"code_sha256":"b5240484210b398a"}},{"arxiv_id":"2306.06546","paper":"/paper/high-fidelity-audio-compression-with-improved","title":"High-Fidelity Audio Compression with Improved RVQGAN","date":"2023-06-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhangxinfd/speechtokenizer","path":"speechtokenizer/model.py","file_url":"https://github.com/zhangxinfd/speechtokenizer/blob/HEAD/speechtokenizer/model.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c360b5ccff704a88","mcp_get_code":{"code_sha256":"c360b5ccff704a88"}}]}