{"id":"https://openalex.org/W7214799051","doi":"https://doi.org/10.48550/arxiv.2609.34292","title":"Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale","display_name":"Pre-registered tests of solid-state-physics-inspired LLM compression: a cluster-level negative result at small-language-model scale","publication_year":2026,"publication_date":"2026-09-28","ids":{"openalex":"https://openalex.org/W7214799051","doi":"https://doi.org/10.48550/arxiv.2609.34292"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.34292","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.34292","pdf_url":"https://arxiv.org/pdf/2609.34292","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.34292","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112781685","display_name":"Junqiang Lu","orcid":"https://orcid.org/0009-0008-4604-9674","observed_orcids":["https://orcid.org/0009-0008-4604-9674"]},"institutions":[{"id":"https://openalex.org/I60388903","display_name":"University of Puerto Rico-Mayaguez","ror":"https://ror.org/00wek6x04","country_code":"PR","type":"education","lineage":["https://openalex.org/I200399037","https://openalex.org/I60388903"]}],"countries":["PR"],"is_corresponding":true,"raw_author_name":"Lu, Jun-qiang","raw_affiliation_strings":["Department of Physics , University of Puerto Rico , Mayag\u00fcez , PR 00680 , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Physics , University of Puerto Rico , Mayag\u00fcez , PR 00680 , USA","institution_ids":["https://openalex.org/I60388903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5112781685"],"corresponding_institution_ids":["https://openalex.org/I60388903"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7714999914169312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.7714999914169312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.03830000013113022,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11804","display_name":"Quantum many-body systems","score":0.022199999541044235,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/language-model-compression","display_name":"language model compression","score":0.9150000214576721},{"id":"https://openalex.org/keywords/one-particle-density-matrix","display_name":"one-body density matrix","score":0.8870000243186951},{"id":"https://openalex.org/keywords/attention-heads","display_name":"attention heads","score":0.6549999713897705},{"id":"https://openalex.org/keywords/matrix-product-operators","display_name":"matrix product operators","score":0.6729999780654907},{"id":"https://openalex.org/keywords/wilsonian-renormalization-group","display_name":"Wilsonian renormalization group","score":0.8669999837875366},{"id":"https://openalex.org/keywords/preregistration","display_name":"preregistration","score":0.39399999380111694},{"id":"https://openalex.org/keywords/negative-results","display_name":"negative results","score":0.7139999866485596},{"id":"https://openalex.org/keywords/gpt-2","display_name":"GPT-2","score":0.6729999780654907}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.6610999703407288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5354999899864197},{"id":"https://openalex.org/C2778217198","wikidata":"https://www.wikidata.org/wiki/Q556977","display_name":"Cutoff","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4487000107765198},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C151376022","wikidata":"https://www.wikidata.org/wiki/Q168698","display_name":"Exponential function","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3603000044822693},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32429999113082886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32420000433921814},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.3091000020503998},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.301800012588501},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2721000015735626},{"id":"https://openalex.org/C139912040","wikidata":"https://www.wikidata.org/wiki/Q937378","display_name":"Logarithmic scale","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C101601086","wikidata":"https://www.wikidata.org/wiki/Q3753228","display_name":"Rank correlation","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C2780339515","wikidata":"https://www.wikidata.org/wiki/Q3074698","display_name":"Arrow","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.257099986076355},{"id":"https://openalex.org/C141141315","wikidata":"https://www.wikidata.org/wiki/Q2379942","display_name":"Guard (computer science)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C124584101","wikidata":"https://www.wikidata.org/wiki/Q1053266","display_name":"Multiplier (economics)","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.34292","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.34292","pdf_url":"https://arxiv.org/pdf/2609.34292","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.34292","doi":"https://doi.org/10.48550/arxiv.2609.34292","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.34292","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.34292","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.34292","pdf_url":"https://arxiv.org/pdf/2609.34292","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309480","display_name":"Nvidia","ror":"https://ror.org/03jdj4y14"},{"id":"https://openalex.org/F4320332618","display_name":"Faculty of Arts and Sciences","ror":"https://ror.org/03vek6s52"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214799051.pdf","grobid_xml":"https://content.openalex.org/works/W7214799051.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1531177993","https://openalex.org/W1555084454","https://openalex.org/W1597171048","https://openalex.org/W1890000358","https://openalex.org/W1922629554","https://openalex.org/W1965675553","https://openalex.org/W1991050432","https://openalex.org/W1993482030","https://openalex.org/W2016407890","https://openalex.org/W2019692968","https://openalex.org/W2037768897","https://openalex.org/W2042938036","https://openalex.org/W2055670190","https://openalex.org/W2058641082","https://openalex.org/W2072565812","https://openalex.org/W2072600048","https://openalex.org/W2075966481","https://openalex.org/W2079216472","https://openalex.org/W2122816100","https://openalex.org/W2142501550","https://openalex.org/W2164805481","https://openalex.org/W2167215970","https://openalex.org/W2246296081","https://openalex.org/W2319680621","https://openalex.org/W2396770278","https://openalex.org/W2511261638","https://openalex.org/W2607839392","https://openalex.org/W2779812635","https://openalex.org/W2785331752","https://openalex.org/W3060669478","https://openalex.org/W3103522166","https://openalex.org/W3136687158","https://openalex.org/W3176468671","https://openalex.org/W3193176826","https://openalex.org/W4283809320","https://openalex.org/W4313484599","https://openalex.org/W4379260375","https://openalex.org/W4381586827","https://openalex.org/W4383174296","https://openalex.org/W4389261532","https://openalex.org/W4389650671","https://openalex.org/W4392780917","https://openalex.org/W4396243492","https://openalex.org/W4399655876","https://openalex.org/W4401024778","https://openalex.org/W4406890872","https://openalex.org/W4407386440","https://openalex.org/W4407764033","https://openalex.org/W4412944812","https://openalex.org/W4415796910","https://openalex.org/W4416111060","https://openalex.org/W7103188877","https://openalex.org/W7106817343","https://openalex.org/W7147465532","https://openalex.org/W7170809026","https://openalex.org/W7197021676"],"related_works":["https://openalex.org/W7161815093","https://openalex.org/W7216331090","https://openalex.org/W7155055265","https://openalex.org/W4406204726","https://openalex.org/W7064709637","https://openalex.org/W7155617954","https://openalex.org/W7172263791","https://openalex.org/W4391272673","https://openalex.org/W4387322997","https://openalex.org/W7196977728"],"abstract_inverted_index":{"We":[0,234],"report":[1],"a":[2,26,48,56,90,105,145],"three-month":[3],"autonomous":[4],"research-agent":[5],"program":[6],"testing":[7],"five":[8],"solid-state-physics-inspired":[9],"compression":[10],"mappings":[11],"on":[12,112],"pretrained":[13],"language":[14],"models,":[15],"with":[16,262],"predictions":[17],"committed":[18],"to":[19,183,210,220,232],"git":[20],"before":[21],"any":[22],"pilot":[23],"data":[24,264],"and":[25,55,104,125,148,172,266],"3-sigma":[27,239],"gate":[28,251],"deciding":[29],"PASS":[30],"or":[31,213],"SHELVE.":[32],"The":[33,194,269],"common":[34],"anchor":[35],"--":[36,46,245,257],"area-law":[37],"/":[38],"Kohn-nearsighted":[39,206],"decay":[40],"of":[41,74,95],"the":[42,81,114,130,149,186,197,216,221,227,236,267],"one-particle":[43],"density":[44],"matrix":[45],"has":[47],"distance":[49],"face":[50,58],"(P001":[51],"Wannier,":[52],"P002":[53],"tight-binding)":[54],"rank":[57,131],"(P003":[59],"DMRG-truncated":[60],"MLPs,":[61],"P005":[62,67],"Wilson-RG,":[63],"P011":[64],"tensor-train":[65,134],"embeddings).":[66],"was":[68,252],"pre-empted":[69],"at":[70,170],"Phase":[71],"1;":[72],"three":[73],"four":[75,258],"Phase-3":[76],"pilots":[77],"were":[78],"falsified.":[79],"On":[80,129],"attention":[82,202],"face,":[83,132],"GPT-2-medium":[84],"attention-versus-distance":[85],"is":[86,102,120,157,218],"best":[87],"fit":[88],"by":[89],"stretched":[91],"exponential":[92],"in":[93],"12":[94],"16":[96],"median-layer":[97],"heads":[98,203],"once":[99],"probe":[100],"padding":[101],"excluded,":[103],"tight-binding":[106],"cutoff":[107],"costs":[108],"+96%":[109],"perplexity":[110],"(P002);":[111],"Pythia-160M":[113],"Wannier":[115],"sparsity":[116],"0.054":[117],"+/-":[118],"0.004":[119],"indistinguishable":[121],"from":[122],"PCA,":[123],"random-Haar":[124],"identity":[126],"baselines":[127],"(P001).":[128],"per-token":[133],"bond":[135],"dimension":[136],"does":[137],"not":[138,255],"track":[139],"surprisal":[140],"(r":[141,163],"=":[142,164,177],"0.016":[143],"vs":[144],"pre-registered":[146,198,259],"0.65)":[147],"format":[150],"inflates":[151],"rather":[152],"than":[153],"compresses":[154],"(P011).":[155],"P003":[156],"mixed:":[158],"its":[159,166,173],"scaling":[160],"claim":[161],"shelved":[162],"-0.434),":[165],"MPO":[167],"premise":[168],"died":[169],"stage-0,":[171],"cross-paper":[174,191],"check,":[175],"r":[176],"0.523":[178],"as":[179],"first":[180],"written,":[181],"collapses":[182],"0.047":[184],"under":[185],"same":[187],"correction,":[188],"leaving":[189],"both":[190],"checks":[192],"null.":[193],"results":[195,261],"invert":[196],"prediction":[199],"that":[200],"most":[201],"behave":[204],"like":[205],"insulators,":[207],"pointing":[208],"instead":[209],"critical,":[211],"glassy":[212],"heavy-tailed":[214],"regimes;":[215],"inversion":[217],"specific":[219],"<=":[222],"350M":[223],"scale":[224],"tested,":[225],"while":[226],"rank-face":[228],"no-gain":[229],"result":[230],"held":[231],"7-8B.":[233],"contribute":[235],"pre-registration":[237],"+":[238,240,242],"cluster-framing":[241],"append-only-catalogue":[243],"discipline":[244],"including":[246],"why":[247],"our":[248],"own":[249],"enforcement":[250],"designed":[253],"but":[254],"deployed":[256],"negative":[260],"full":[263],"release,":[265],"inversion.":[268],"catalogue":[270],"holds":[271],"eighteen":[272],"concluded":[273],"studies,":[274],"seventeen":[275],"negative.":[276]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-09-30T00:00:00"}