{"id":"https://openalex.org/W7135094319","doi":"https://doi.org/10.48550/arxiv.2603.10000","title":"Beyond the Prompt in Large Language Models: Comprehension, In-Context Learning, and Chain-of-Thought","display_name":"Beyond the Prompt in Large Language Models: Comprehension, In-Context Learning, and Chain-of-Thought","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7135094319","doi":"https://doi.org/10.48550/arxiv.2603.10000"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.10000","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10000","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,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.10000","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122977626","display_name":"Yuling Jiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiao, Yuling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128913318","display_name":"Yanming Lai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lai, Yanming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128855912","display_name":"Huazhen Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Huazhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113380877","display_name":"Wensen Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Wensen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115593562","display_name":"Houduo Qi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi, Houduo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128831936","display_name":"Defeng Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Defeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":0.19859999418258667,"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":0.19859999418258667,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.13680000603199005,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.10740000009536743,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.7502999901771545},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5443999767303467},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.539900004863739},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.47369998693466187},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.4674000144004822},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4194999933242798},{"id":"https://openalex.org/keywords/empirical-evidence","display_name":"Empirical evidence","score":0.3630000054836273},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.36239999532699585}],"concepts":[{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.7502999901771545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6359000205993652},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5443999767303467},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.539900004863739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48980000615119934},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.47369998693466187},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4194999933242798},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4000000059604645},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3781999945640564},{"id":"https://openalex.org/C166052673","wikidata":"https://www.wikidata.org/wiki/Q83021","display_name":"Empirical evidence","level":2,"score":0.3630000054836273},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C194232998","wikidata":"https://www.wikidata.org/wiki/Q1606712","display_name":"Transition (genetics)","level":3,"score":0.304500013589859},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30309998989105225},{"id":"https://openalex.org/C2776544517","wikidata":"https://www.wikidata.org/wiki/Q189447","display_name":"Unexpected events","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2662000060081482},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C188147891","wikidata":"https://www.wikidata.org/wiki/Q147638","display_name":"Cognitive science","level":1,"score":0.2533999979496002},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.10000","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10000","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,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.10000","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.10000","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,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.42369890213012695,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"have":[4],"demonstrated":[5],"remarkable":[6],"proficiency":[7],"across":[8,119],"diverse":[9],"tasks,":[10],"exhibiting":[11],"emergent":[12],"properties":[13],"such":[14],"as":[15],"semantic":[16],"prompt":[17,59,133,191],"comprehension,":[18],"In-Context":[19],"Learning":[20],"(ICL),":[21],"and":[22,83,135],"Chain-of-Thought":[23],"(CoT)":[24],"reasoning.":[25],"Despite":[26],"their":[27,176],"empirical":[28],"success,":[29],"the":[30,43,105,114,140,150,166,171,186],"theoretical":[31,183],"mechanisms":[32],"driving":[33],"these":[34,46],"phenomena":[35],"remain":[36],"poorly":[37],"understood.":[38],"This":[39],"study":[40],"dives":[41],"into":[42,159,185],"foundations":[44],"of":[45,111,162,189],"observations":[47],"by":[48,131],"addressing":[49],"three":[50],"critical":[51],"questions:":[52],"(1)":[53],"How":[54],"do":[55,86],"LLMs":[56,108],"accurately":[57],"decode":[58],"semantics":[60],"despite":[61],"being":[62],"trained":[63],"solely":[64],"on":[65,139],"a":[66,160],"next-token":[67],"prediction":[68],"objective?":[69],"(2)":[70],"Through":[71],"what":[72],"mechanism":[73],"does":[74],"ICL":[75,128],"facilitate":[76],"performance":[77,130],"gains":[78],"without":[79],"explicit":[80],"parameter":[81],"updates?":[82],"(3)":[84],"Why":[85],"intermediate":[87],"reasoning":[88],"steps":[89],"in":[90],"CoT":[91,147],"prompting":[92,148],"effectively":[93],"unlock":[94],"capabilities":[95],"for":[96,153],"complex,":[97],"multi-step":[98],"problems?":[99],"Our":[100],"results":[101],"demonstrate":[102],"that,":[103],"through":[104],"autoregressive":[106],"process,":[107],"are":[109],"capable":[110],"exactly":[112],"inferring":[113],"transition":[115],"probabilities":[116],"between":[117],"tokens":[118],"distinct":[120],"tasks":[121],"using":[122],"provided":[123],"prompts.":[124],"We":[125],"show":[126],"that":[127,146,165],"enhances":[129],"reducing":[132],"ambiguity":[134],"facilitating":[136],"posterior":[137],"concentration":[138],"intended":[141],"task.":[142],"Furthermore,":[143],"we":[144,180],"find":[145],"activates":[149],"model's":[151],"capacity":[152],"task":[154],"decomposition,":[155],"breaking":[156],"complex":[157],"problems":[158],"sequence":[161],"simpler":[163],"sub-tasks":[164],"model":[167],"has":[168],"mastered":[169],"during":[170],"pretraining":[172],"phase.":[173],"By":[174],"comparing":[175],"individual":[177],"error":[178],"bounds,":[179],"provide":[181],"novel":[182],"insights":[184],"statistical":[187],"superiority":[188],"advanced":[190],"engineering":[192],"techniques.":[193]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-13T00:00:00"}