{"id":"https://openalex.org/W7134853355","doi":"https://doi.org/10.48550/arxiv.2603.07023","title":"Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment","display_name":"Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134853355","doi":"https://doi.org/10.48550/arxiv.2603.07023"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07023","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Liu, Junming","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Junming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128660302","display_name":"Yuqi Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yuqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128673276","display_name":"Shiping Wen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Shiping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128680818","display_name":"Zhigang Zeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zeng, Zhigang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128637883","display_name":"Tingwen Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Tingwen","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29242857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.5753999948501587,"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":0.5753999948501587,"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":0.2443999946117401,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.028599999845027924,"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/robustness","display_name":"Robustness (evolution)","score":0.5996999740600586},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5325999855995178},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.48420000076293945},{"id":"https://openalex.org/keywords/preference","display_name":"Preference","score":0.48260000348091125},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/cognition","display_name":"Cognition","score":0.37709999084472656},{"id":"https://openalex.org/keywords/causal-reasoning","display_name":"Causal reasoning","score":0.3479999899864197},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.3337000012397766}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6220999956130981},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5996999740600586},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5982999801635742},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5325999855995178},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.48420000076293945},{"id":"https://openalex.org/C2781249084","wikidata":"https://www.wikidata.org/wiki/Q908656","display_name":"Preference","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44519999623298645},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C115086926","wikidata":"https://www.wikidata.org/wiki/Q17004651","display_name":"Causal reasoning","level":3,"score":0.3479999899864197},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.32350000739097595},{"id":"https://openalex.org/C76188268","wikidata":"https://www.wikidata.org/wiki/Q1783165","display_name":"Context effect","level":3,"score":0.311599999666214},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C2779525943","wikidata":"https://www.wikidata.org/wiki/Q1187300","display_name":"Grammaticality","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.2732999920845032},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C2780211513","wikidata":"https://www.wikidata.org/wiki/Q1132167","display_name":"Discernment","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2639000117778778},{"id":"https://openalex.org/C43971567","wikidata":"https://www.wikidata.org/wiki/Q3142865","display_name":"Logical reasoning","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07023","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07023","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07023","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"pmh:doi:10.48550/arxiv.2603.07023","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7452927231788635}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,15,45,80,137],"promise":[2],"of":[3,47,82],"Retrieval-Augmented":[4],"Generation":[5],"in":[6,31,150],"grounding":[7],"Multimodal":[8],"Large":[9],"Language":[10],"Models":[11],"with":[12],"external":[13,83],"knowledge,":[14],"transition":[16],"to":[17,22,37,66,96,116,135],"extensive":[18],"contexts":[19],"often":[20],"leads":[21],"significant":[23],"attention":[24],"dilution":[25],"and":[26,142],"reasoning":[27,118,144],"hallucinations.":[28],"The":[29],"surge":[30],"information":[32,98],"density":[33],"causes":[34],"critical":[35],"evidence":[36,84],"be":[38],"submerged":[39],"by":[40],"voluminous":[41],"noise,":[42],"which":[43],"complicates":[44],"discernment":[46],"relevant":[48],"fragments":[49],"within":[50],"a":[51,60,72],"dense":[52],"input.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"\\textbf{Hit-RAG},":[59],"multi-stage":[61],"preference":[62],"alignment":[63],"framework":[64],"designed":[65],"resolve":[67],"these":[68],"cognitive":[69],"bottlenecks":[70],"through":[71],"progressive":[73],"optimization":[74],"pipeline.":[75],"Our":[76],"approach":[77],"systematically":[78],"refines":[79],"utilization":[81],"via":[85],"three":[86],"distinct":[87],"stages.":[88],"First,":[89],"Supervised":[90],"Fine-tuning":[91],"establishes":[92],"baseline":[93],"context":[94,140],"awareness":[95],"minimize":[97],"neglect.":[99],"Next,":[100],"Discriminative":[101],"Preference":[102],"Alignment":[103],"enhances":[104],"robustness":[105],"against":[106],"misleading":[107],"distractors.":[108],"Finally,":[109],"Group-Relative":[110],"Policy":[111],"Optimization":[112],"stabilizes":[113],"logical":[114],"synthesis":[115],"prevent":[117],"collapse.":[119],"Extensive":[120],"evaluations":[121],"on":[122],"eight":[123],"benchmarks":[124],"demonstrate":[125],"that":[126],"Hit-RAG":[127],"consistently":[128],"yields":[129],"substantial":[130],"performance":[131],"gains,":[132],"enabling":[133],"models":[134],"bridge":[136],"gap":[138],"between":[139],"acquisition":[141],"accurate":[143],"while":[145],"surpassing":[146],"much":[147],"larger":[148],"counterparts":[149],"long-context":[151],"scenarios.":[152]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}
