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https://www.amazon.science/locations/aachendaily0.00 https://www.amazon.science/locations/tel-aviv-and-haifadaily0.00 https://www.amazon.science/locations/luxembourgdaily0.00 https://www.amazon.science/locations/london-and-cambridgedaily0.00 https://www.amazon.science/locations/edinburghdaily0.00 https://www.amazon.science/locations/los-angelesdaily0.00 https://www.amazon.science/locations/san-diegodaily0.00 https://www.amazon.science/locations/san-francisco-bay-areadaily0.00 https://www.amazon.science/locations/boston-cambridge-and-north-readingdaily0.00 https://www.amazon.science/locations/new-york-citydaily0.00 https://www.amazon.science/locations/pittsburghdaily0.00 https://www.amazon.science/locations/arlington-herndondaily0.00 https://www.amazon.science/locations/seattle-and-bellevuedaily0.00 https://www.amazon.science/author/pieter-abbeeldaily0.00 https://www.amazon.science/author/jose-blanchetdaily0.00 https://www.amazon.science/author/mark-lewisdaily0.00 https://www.amazon.science/author/marco-giomettodaily0.00 https://www.amazon.science/author/susan-murphydaily0.00 https://www.amazon.science/author/alexey-gorshkovdaily0.00 https://www.amazon.science/author/michael-wagnerdaily0.00 https://www.amazon.science/author/don-porterdaily0.00 https://www.amazon.science/author/dilek-hakkani-turdaily0.00 https://www.amazon.science/author/guanya-shidaily0.00 https://www.amazon.science/blog/amazon-scholar-solves-century-old-problem-with-automated-reasoningdaily0.00 https://www.amazon.science/news-and-features/amazon-and-ucla-announce-2023-science-hub-awardsdaily0.00 https://www.amazon.science/tag/awsdaily0.00 https://www.amazon.science/tag/firecrackerdaily0.00 https://www.amazon.science/blog/demystifying-agentsdaily0.00 https://www.amazon.science/blog/how-controllers-from-industrial-machinery-can-coordinate-multitask-machine-learningdaily0.00 https://www.amazon.science/publications/speed-without-sacrifice-fine-tuning-language-models-with-medusa-and-knowledge-distillation-in-travel-applicationsdaily0.00 https://www.amazon.science/blog/diverse-reasoning-traces-teach-llms-to-make-better-decisionsdaily0.00 https://www.amazon.science/author/sheng-jiadaily0.00 https://www.amazon.science/author/xiao-wangdaily0.00 https://www.amazon.science/publications/bmojo-hybrid-state-space-realizations-of-foundation-models-with-eidetic-and-fading-memorydaily0.00 https://cdn.amazon.science/fe/a4/10a1dab44492b8acac96ebe38375/scipub-approval152134-48351915-qasp-queryadaptive-robust-vector-search-policy.pdfdaily0.00 https://www.amazon.science/publications/mailto:?body=QASP%3A%20Query-adaptive%20robust%20vector%20search%20policy%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fpublications%2Fqasp-query-adaptive-robust-vector-search-policy%0A%0AA%20fundamental%20challenge%20of%20vector%20search%20is%20achieving%20consistently%20high%20recall%20while%20minimizing%20computational%20costs.%20Fixed%20search%20parameters%20cause%20significant%20performance%20variance%20across%20queries%2C%20and%20conventional%20evaluation%20on%20average%20recall%20masks%20these%20per-query%20disparities.%20We%20introduce%20QASP%20%28Query-Adaptive%20robust%20vector%20Search%20Policy%29%2C%20which%20predicts%20the%20complete%20recall%20progression%20curve%20per%20query%20viadaily0.00 https://social-plugins.line.me/lineit/share?url=https://www.amazon.science/publications/qasp-query-adaptive-robust-vector-search-policydaily0.00 https://www.reddit.com/submit?url=https://www.amazon.science/publications/qasp-query-adaptive-robust-vector-search-policy&title=QASP: Query-adaptive robust vector search policydaily0.00 http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/publications/qasp-query-adaptive-robust-vector-search-policy&title=QASP: Query-adaptive robust vector search policy&summary=A fundamental challenge of vector search is achieving consistently high recall while minimizing computational costs. Fixed search parameters cause significant performance variance across queries, and conventional evaluation on average recall masks these per-query disparities. We introduce QASP (Query-Adaptive robust vector Search Policy), which predicts the complete recall progression curve per query viadaily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/publications/qasp-query-adaptive-robust-vector-search-policydaily0.00 https://api.whatsapp.com/send?text=QASP: Query-adaptive robust vector search policy%20https://www.amazon.science/publications/qasp-query-adaptive-robust-vector-search-policydaily0.00 https://www.amazon.science/tag/searchdaily0.00 https://www.amazon.science/tag/transfer-learningdaily0.00 https://www.amazon.science/tag/zero-shot-learningdaily0.00 https://www.amazon.science/publications/unsupervised-multi-modal-representation-learning-for-high-quality-retrieval-of-similar-products-at-e-commerce-scaledaily0.00 https://www.amazon.science/author/jinyu-yangdaily0.00 https://www.amazon.science/author/shioulin-samdaily0.00 https://www.amazon.science/author/anoop-s-v-k-k-saladidaily0.00 https://www.amazon.science/conferences-and-events/iclr-2026daily0.00 https://cdn.amazon.science/07/f4/435a309d41cb9337c4afa8c65d9c/scipub-approval152129-50101305-unified-crossdomain-semantic-retrieval-for-coldstart-audiobook-discovery.pdfdaily0.00 https://www.amazon.science/publications/mailto:?body=Unified%20cross-domain%20semantic%20retrieval%20for%20cold-start%20audiobook%20discovery%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fpublications%2Funified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discovery%0A%0ARecommending%20a%20new%20content%20type%20to%20users%20who%20have%20never%20tried%20it%20is%20a%20hard%20cold-start%20problem%3A%20there%20is%20no%20in-domain%20history%20to%20infer%20taste%20from.%20We%20study%20audiobook%20discovery%20on%20a%20large%20music%20streaming%20platform%2C%20where%20most%20users%20have%20never%20played%20an%20audiobook.%20Many%20of%20them%2C%20however%2C%20leave%20behavioral%20traces%20in%20other%20domains%3A%20podcasts%2C%20audiobooks%20elsewhere%2C%20videos%2C%20and%20related%20content.%20We%20turn%20those%20tracesdaily0.00 https://social-plugins.line.me/lineit/share?url=https://www.amazon.science/publications/unified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discoverydaily0.00 https://www.reddit.com/submit?url=https://www.amazon.science/publications/unified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discovery&title=Unified cross-domain semantic retrieval for cold-start audiobook discoverydaily0.00 http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/publications/unified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discovery&title=Unified cross-domain semantic retrieval for cold-start audiobook discovery&summary=Recommending a new content type to users who have never tried it is a hard cold-start problem: there is no in-domain history to infer taste from. We study audiobook discovery on a large music streaming platform, where most users have never played an audiobook. Many of them, however, leave behavioral traces in other domains: podcasts, audiobooks elsewhere, videos, and related content. We turn those tracesdaily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/publications/unified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discoverydaily0.00 https://api.whatsapp.com/send?text=Unified cross-domain semantic retrieval for cold-start audiobook discovery%20https://www.amazon.science/publications/unified-cross-domain-semantic-retrieval-for-cold-start-audiobook-discoverydaily0.00 https://cdn.amazon.science/f1/d5/342871a14ff496527baf86943712/scipub-approval152129-50882652-from-expert-coding-to-expert-steering-zeroshot-tlf-generation-with-agentic-ai.pdfdaily0.00 https://www.amazon.science/publications/mailto:?body=From%20expert%20coding%20to%20expert%20steering%3A%20Zero-shot%20TLF%20generation%20with%20agentic%20AI%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fpublications%2Ffrom-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-ai%0A%0AProducing%20Tables%2C%20Listings%2C%20and%20Figures%20%28TLFs%29%20remains%20one%20of%20the%20most%20important%20and%20expert-dependent%20steps%20in%20clinical%20study%20reporting.%20In%20a%2010-week%20proof%20of%20concept%2C%20AI%20engineers%20from%20AWS%20and%20statistical%20programmers%20from%20Bayer%20jointly%20build%20a%20zero-shot%2C%20multi-agent%20workflow%20that%20generates%20structured%20work%20packages%2C%20executable%20R%20code%2C%20and%20draft%20TLFs%20with%20automated%20checks%20and%20human%20review.%20Developed%20on%20adaily0.00 https://social-plugins.line.me/lineit/share?url=https://www.amazon.science/publications/from-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-aidaily0.00 https://www.reddit.com/submit?url=https://www.amazon.science/publications/from-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-ai&title=From expert coding to expert steering: Zero-shot TLF generation with agentic AIdaily0.00 http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/publications/from-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-ai&title=From expert coding to expert steering: Zero-shot TLF generation with agentic AI&summary=Producing Tables, Listings, and Figures (TLFs) remains one of the most important and expert-dependent steps in clinical study reporting. In a 10-week proof of concept, AI engineers from AWS and statistical programmers from Bayer jointly build a zero-shot, multi-agent workflow that generates structured work packages, executable R code, and draft TLFs with automated checks and human review. Developed on adaily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/publications/from-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-aidaily0.00 https://api.whatsapp.com/send?text=From expert coding to expert steering: Zero-shot TLF generation with agentic AI%20https://www.amazon.science/publications/from-expert-coding-to-expert-steering-zero-shot-tlf-generation-with-agentic-aidaily0.00 https://cdn.amazon.science/f1/36/4f2e2ec94f96860b1ab05db6030d/scipub-approval152129-50361238-robust-estimation-of-prior-parameters-in-normalnormal-empirical-bayes.pdfdaily0.00 https://www.amazon.science/publications/mailto:?body=Robust%20estimation%20of%20prior%20parameters%20in%20normal-normal%20empirical%20Bayes%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fpublications%2Frobust-estimation-of-prior-parameters-in-normal-normal-empirical-bayes%0A%0AMany%20large-scale%20A%2FB%20testing%20systems%20leverage%20normal-normal%20empirical%20Bayes%20models%20to%20improve%20estimates%20of%20treatment%20impacts%20and%20launch%20decisions.%20We%20show%20that%20in%20these%20models%20maximum%20likelihood%20estimates%20of%20the%20variance%20of%20true%20impacts%20can%20be%20sensitive%20to%20a%20small%20number%20of%20extreme%20observations.%20We%20propose%20a%20bounded%20influence%20maximum%20likelihood%20estimator%20%28BIMLE%29%20that%20downweights%20such%20observations%20in%20proportiondaily0.00 https://social-plugins.line.me/lineit/share?url=https://www.amazon.science/publications/robust-estimation-of-prior-parameters-in-normal-normal-empirical-bayesdaily0.00 https://www.reddit.com/submit?url=https://www.amazon.science/publications/robust-estimation-of-prior-parameters-in-normal-normal-empirical-bayes&title=Robust estimation of prior parameters in normal-normal empirical Bayesdaily0.00 http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/publications/robust-estimation-of-prior-parameters-in-normal-normal-empirical-bayes&title=Robust estimation of prior parameters in normal-normal empirical Bayes&summary=Many large-scale A/B testing systems leverage normal-normal empirical Bayes models to improve estimates of treatment impacts and launch decisions. We show that in these models maximum likelihood estimates of the variance of true impacts can be sensitive to a small number of extreme observations. We propose a bounded influence maximum likelihood estimator (BIMLE) that downweights such observations in proportiondaily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/publications/robust-estimation-of-prior-parameters-in-normal-normal-empirical-bayesdaily0.00 https://api.whatsapp.com/send?text=Robust estimation of prior parameters in normal-normal empirical Bayes%20https://www.amazon.science/publications/robust-estimation-of-prior-parameters-in-normal-normal-empirical-bayesdaily0.00 https://cdn.amazon.science/fb/4f/e3c9026a4337b49b6c7fa77f112c/scipub-approval152129-48180628-prochunker-selfoptimizing-procedural-chunking-for-agentready-workflow-graphs.pdfdaily0.00 https://www.amazon.science/publications/mailto:?body=ProChunker%3A%20Self-optimizing%20procedural%20chunking%20for%20agent-ready%20workflow%20graphs%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fpublications%2Fprochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphs%0A%0ACan%20an%20LLM%20read%20a%2030%2B%20page%20Standard%20Operating%20Procedure%20%28SOP%29%20and%20produce%20a%20team%20of%20agents%20that%20reliably%20execute%20it%3F%20Industrial%20SOPs%20bury%20workflow%20logic%20in%20prose%2C%20leave%20inter-step%20dependencies%20implicit%2C%20and%20scatter%20referenced%20entities%20across%20sections%2C%20forcing%20planners%20to%20parse%2C%20sequence%2C%20and%20tool-map%20within%20one%20context%20window.%20We%20argue%20that%20the%20missing%20primitive%20is%20procedural%20chunking%20%3A%20decomposing%20a%20documentdaily0.00 https://social-plugins.line.me/lineit/share?url=https://www.amazon.science/publications/prochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphsdaily0.00 https://www.reddit.com/submit?url=https://www.amazon.science/publications/prochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphs&title=ProChunker: Self-optimizing procedural chunking for agent-ready workflow graphsdaily0.00 http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/publications/prochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphs&title=ProChunker: Self-optimizing procedural chunking for agent-ready workflow graphs&summary=Can an LLM read a 30+ page Standard Operating Procedure (SOP) and produce a team of agents that reliably execute it? Industrial SOPs bury workflow logic in prose, leave inter-step dependencies implicit, and scatter referenced entities across sections, forcing planners to parse, sequence, and tool-map within one context window. We argue that the missing primitive is procedural chunking : decomposing a documentdaily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/publications/prochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphsdaily0.00 https://api.whatsapp.com/send?text=ProChunker: Self-optimizing procedural chunking for agent-ready workflow graphs%20https://www.amazon.science/publications/prochunker-self-optimizing-procedural-chunking-for-agent-ready-workflow-graphsdaily0.00 https://www.amazon.science/publications/agent-ops-a-multi-agent-orchestration-framework-for-end-to-end-sop-automation-in-e-commerce-operationsdaily0.00 https://www.amazon.science/author/apoorva-singhdaily0.00 https://www.amazon.science/conferences-and-events/acl-2026daily0.00 https://www.amazon.science/author/vivek-sembiumdaily0.00 https://www.amazon.science/author/vijit-malikdaily0.00 https://www.amazon.science/author/anirban-majumderdaily0.00 https://www.amazon.science/conferences-and-events/emnlp-2024daily0.00 https://www.amazon.science/publications/merit-mitigating-exposure-bias-in-generative-xmc-for-user-interest-propensity-modelingdaily0.00 https://www.amazon.science/author/sachin-farfadedaily0.00 https://www.amazon.science/author/prakash-mandayam-comar?p=2daily0.00 https://www.amazon.science/author/deepak-guptadaily0.00 https://www.amazon.science/author/shervin-malmasidaily0.00 https://www.amazon.science/author/suleiman-khandaily0.00 https://www.amazon.science/author/antonio-purificatodaily0.00 https://www.amazon.science/author/andrea-bacciudaily0.00 https://www.amazon.science/author/amin-mantrachdaily0.00 https://www.amazon.science/author/sahika-gencdaily0.00 https://www.amazon.science/author/minhua-lindaily0.00 https://www.amazon.science/author/zhan-shidaily0.00 https://www.amazon.science/author/yisi-sangdaily0.00 https://www.amazon.science/author/bing-hedaily0.00 https://www.amazon.science/author/zewen-liudaily0.00 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In this year’s Competition track student teams will focus on secure multi-turn development of web applications using coding assistants. Each team will take on the role of either a ‘model developer’ or ‘red team’. The model developer teams will focus on building LLM-driven coding assistants that can complete complex software engineering tasks to modify and extend full stack web applications. In addition to adding capabilities, coding assistants built by model developer teams must prevent accidental or purposeful introduction of security vulnerabilities into the application. To this end, model developer teams will also build bots that simulate malicious users. They will use these malicious user bots to test their systems and then use these same bots to test the resilience of opposing model developer teams during the Competition. daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/nova-ai-challenge/rulesdaily0.00 https://api.whatsapp.com/send?text=Amazon Nova AI Challenge: Trusted Software Agents, Rules%20https://www.amazon.science/nova-ai-challenge/rulesdaily0.00 https://www.amazon.science/nova-ai-challenge/mailto:amazon-challenge@amazon.comdaily0.00 https://www.amazon.science/nova-ai-challenge/teams?p=1daily0.00 https://www.amazon.science/tag/internshipsdaily0.00 https://www.amazon.science/?00000189-7086-df5d-a7e9-75965e7b0001-page=2daily0.00 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http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/news/amazon-and-carnegie-mellon-university-launch-strategic-ai-innovation-hub&title=Amazon and Carnegie Mellon University launch strategic AI Innovation Hub&summary=The collaboration will advance research in generative AI, robotics, natural-language processing and cloud computing while fostering innovation in foundational and emerging technologies.daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/news/amazon-and-carnegie-mellon-university-launch-strategic-ai-innovation-hubdaily0.00 https://api.whatsapp.com/send?text=Amazon and Carnegie Mellon University launch strategic AI Innovation Hub%20https://www.amazon.science/news/amazon-and-carnegie-mellon-university-launch-strategic-ai-innovation-hubdaily0.00 https://www.amazon.science/author/swaminathan-sivasubramaniandaily0.00 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http://sns.qzone.qq.com/cgi-bin/qzshare/cgi_qzshare_onekey?url=https://www.amazon.science/academic-engagements/columbia-engineering-and-amazon-announce-creation-of-new-york-research-center&title=Columbia Engineering and Amazon announce creation of New York research center&summary=Columbia Center of Artificial Intelligence Technology focuses on advancing innovation in artificial intelligence technologies.daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/academic-engagements/columbia-engineering-and-amazon-announce-creation-of-new-york-research-centerdaily0.00 https://api.whatsapp.com/send?text=Columbia Engineering and Amazon announce creation of New York research center%20https://www.amazon.science/academic-engagements/columbia-engineering-and-amazon-announce-creation-of-new-york-research-centerdaily0.00 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Science Hub to exist outside the US will focus on driving AI research and development throughout Germany.daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/academic-engagements/amazon-and-max-planck-society-launch-science-hubdaily0.00 https://api.whatsapp.com/send?text=Amazon and Max Planck Society launch Science Hub%20https://www.amazon.science/academic-engagements/amazon-and-max-planck-society-launch-science-hubdaily0.00 https://www.amazon.science/academic-engagements/nulldaily0.00 https://www.amazon.science/latest-news/amazons-fourth-r-d-center-in-germany-is-dedicated-to-open-ai-researchdaily0.00 https://www.amazon.science/tag/max-planck-societydaily0.00 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efforts in areas of mutual interest, beginning with artificial intelligence and robotics.daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/academic-engagements/amazon-and-mit-establish-science-hubdaily0.00 https://api.whatsapp.com/send?text=Amazon and MIT establish Science Hub%20https://www.amazon.science/academic-engagements/amazon-and-mit-establish-science-hubdaily0.00 https://www.amazon.science/academic-engagements/winning-last-mile-challenge-team-addresses-problem-of-combining-mathematical-routes-with-driver-knowledgedaily0.00 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of data, which don’t have enough space to enable memorization.daily0.00 https://service.weibo.com/share/share.php?url=https://www.amazon.science/blog/why-dont-machine-learning-research-agents-overfitdaily0.00 https://api.whatsapp.com/send?text=Why don’t machine learning research agents overfit?%20https://www.amazon.science/blog/why-dont-machine-learning-research-agents-overfitdaily0.00 https://www.amazon.science/tag/language-modelsdaily0.00 https://www.amazon.science/blog/mailto:?body=Developing%20provably%20correct%20Rust%20code%20with%20Verus%0A%0Ahttps%3A%2F%2Fwww.amazon.science%2Fblog%2Fdeveloping-provably-correct-rust-code-with-verus%0A%0AHow%20the%20Verus%20%22program%20verifier%22%2C%20which%20automatically%20checks%20code%20against%20a%20mathematical%20specification%20of%20its%20functionality%2C%20helps%20increase%20security%20assurance%20in%20software%20projects.daily0.00 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