{"id":"https://openalex.org/W4408353419","doi":"https://doi.org/10.1109/icassp49660.2025.10889432","title":"Enhancing Long-Term Capabilities of Large Language Models via Discourse Sub-graph Analysis","display_name":"Enhancing Long-Term Capabilities of Large Language Models via Discourse Sub-graph Analysis","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408353419","doi":"https://doi.org/10.1109/icassp49660.2025.10889432"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10889432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033846632","display_name":"Zhenyu Guan","orcid":"https://orcid.org/0009-0005-7601-7380"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Guan","raw_affiliation_strings":["Renmin University of China, CHN,School of Information,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, CHN,School of Information,Beijing,China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020649203","display_name":"Xun Liang","orcid":"https://orcid.org/0000-0002-3431-5954"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xun Liang","raw_affiliation_strings":["Renmin University of China, CHN,School of Information,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, CHN,School of Information,Beijing,China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101600324","display_name":"Sensen Zhang","orcid":"https://orcid.org/0000-0002-0449-4699"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sensen Zhang","raw_affiliation_strings":["Renmin University of China, CHN,School of Information,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, CHN,School of Information,Beijing,China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02616192,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9616000056266785,"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":0.9616000056266785,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9143999814987183,"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/computer-science","display_name":"Computer science","score":0.7093780636787415},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.6942107677459717},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.451255202293396},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24072733521461487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7093780636787415},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6942107677459717},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.451255202293396},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24072733521461487},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10889432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10889432","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2896457183","https://openalex.org/W2963926728","https://openalex.org/W3019913914","https://openalex.org/W4253028564","https://openalex.org/W4318960851","https://openalex.org/W4393145623","https://openalex.org/W4393157465","https://openalex.org/W4401023606","https://openalex.org/W4404781337","https://openalex.org/W6682631176","https://openalex.org/W6766673545","https://openalex.org/W6769627184","https://openalex.org/W6771915120","https://openalex.org/W6781533629","https://openalex.org/W6793886675","https://openalex.org/W6855665169"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"The":[0],"rapid":[1],"advancement":[2],"of":[3,47,52,109],"Large":[4],"Language":[5],"ModelS":[6],"(LLMs)":[7],"has":[8],"inaugurated":[9],"a":[10,39],"transformative":[11],"era":[12],"in":[13,20],"natural":[14,72],"language":[15,73],"processing,":[16],"fostering":[17],"unprecedented":[18],"capabilities":[19],"text":[21],"generation,":[22],"understanding,":[23],"and":[24,55,95],"contextual":[25],"analysis.":[26],"However,":[27],"effectively":[28],"handling":[29],"extensive":[30],"contexts,":[31],"which":[32],"are":[33],"crucial":[34],"for":[35],"many":[36],"applications,":[37],"remains":[38],"significant":[40],"challenge":[41],"due":[42],"to":[43,75],"the":[44,48,53,56,107,110],"intrinsic":[45],"limitations":[46],"context":[49,79],"window":[50],"sizes":[51],"models":[54],"computational":[57,93],"burdens":[58],"associated":[59],"with":[60],"their":[61],"operations.":[62],"This":[63],"study":[64],"proposes":[65],"an":[66],"innovative":[67],"framework":[68,90],"that":[69,88],"uses":[70],"unsupervised":[71],"summarization":[74],"provide":[76],"more":[77],"efficient":[78],"handling.":[80],"Our":[81],"methodology":[82],"is":[83],"dubbed":[84],"LONGPC.":[85],"We":[86],"demonstrate":[87],"our":[89],"significantly":[91],"reduces":[92],"overhead":[94],"enhances":[96],"LLMs\u2019":[97],"performance":[98],"across":[99],"various":[100],"datasets":[101],"while":[102],"maintaining":[103],"or":[104],"even":[105],"enhancing":[106],"quality":[108],"generated":[111],"content.":[112]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
