{"article":{"annotation":{"article_id":"multi-agent-session-alternation-tests-machine-learning-engineering","available_at":"2026-10-13T00:52:16.046437Z","geography_revision":"ef6ee0010dda5fe7b240fd514749b43e214c57da73222d2e40ec83b276dd0977","id":"cbbb7175821fee0a13e298e7658e769e66dc065fcb79ddbe76a37e62f8a3318e","input_sha256":"6512fc4c0224e8bbcd7e6c2fe728a9633e4e5132f1585ebabdad6bd6aba48848","limitations":["Rule-derived subjects are candidates, not verified editorial labels or calibrated model probabilities.","Coverage is distinct from event location. Unknown country/city/coordinates remain absent; no automatic geocoding.","Article geometries keep their stated precision and methodology; reproducing them is not independent coordinate verification."],"method":"controlled-rules-v1","places":[{"admin1":null,"city":null,"coordinate_note":null,"coordinate_reference_system":"OGC:CRS84","coordinate_source":null,"country":"CN","evidence":[{"field":"country","language":"en","note":"Explicit preserved editorial country/region; no city or national centroid inferred","source_urls":["https://arxiv.org/html/2610.13494v1"]}],"geometry":null,"id":"iso3166-1:CN","kind":"country-or-area","labels":{"ar":"الصين","en":"China","es":"China","fr":"Chine"},"match_status":"candidate","precision":"regional","role":"coverage","uncertainty_m":null}],"rules_sha256":"fb5ad3c27c91cb840f7a0a05f7f64a5cb26ad0374409ff9457f277c7092e22b4","schema_version":1,"subjects":[{"concept_id":"medtop:13000000","confidence":null,"confidence_method":null,"evidence":[{"field":"category+topics","language":"en","note":"Preserved editorial category/topic; broad candidate only","source_urls":["https://arxiv.org/html/2610.13494v1"]}],"method":"controlled-rules-v1","rule_id":"technology-broad","status":"candidate"}],"taxonomy_revision":"1f2db31d811fca07e99b16d402c10e2cc2965c9df1c7b41d9be348b40a24e7fb","taxonomy_version":"IPTC Media Topics 2026-Q2"},"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=es","category":"technology","content":{"key_points":[],"paragraphs":["Investigadores vinculados a Tsinghua, Zhejiang y NVIDIA presentaron Humanize MLE Agents, un método que alterna las sesiones de dos agentes en tareas largas de ingeniería de aprendizaje automático. Cada sesión se detiene tras un número limitado de experimentos; el contexto se reinicia entre sesiones, mientras el código, los modelos y los resultados anteriores permanecen en un espacio de trabajo común.","En 75 tareas de Kaggle de MLE-bench, los autores informan de una tasa del 78,2 % de obtención de alguna medalla y afirman que el flujo superó la mejor referencia de código abierto con menor presupuesto de tiempo. Es un resultado de ese conjunto de concursos y esas configuraciones de agentes; no garantiza la misma mejora en otras versiones de modelos ni en proyectos reales."],"sections":[]},"corrections":[],"country":"CN","data":{"blocks":[{"columns":[{"key":"metric","label":{"ar":"المقياس","de":"Messgröße","en":"Measure","es":"Medida","fr":"Mesure","pt":"Medida","tr":"Ölçüt"},"language":"en","type":"text"},{"key":"value","label":{"ar":"القيمة المعلنة","de":"Berichteter Wert","en":"Reported value","es":"Valor comunicado","fr":"Valeur rapportée","pt":"Valor informado","tr":"Bildirilen değer"},"type":"number","unit":"percent"},{"key":"scope","label":{"ar":"نطاق التجربة","de":"Versuchsumfang","en":"Experimental scope","es":"Alcance experimental","fr":"Périmètre expérimental","pt":"Escopo experimental","tr":"Deney kapsamı"},"language":"en","type":"text"}],"description":{"ar":"75 مهمة Kaggle؛ تقييم MLE-bench","de":"75 Kaggle-Aufgaben; MLE-bench-Auswertung","en":"75 Kaggle tasks; MLE-bench evaluation","es":"75 tareas de Kaggle; evaluación MLE-bench","fr":"75 tâches Kaggle; évaluation MLE-bench","pt":"75 tarefas do Kaggle; avaliação MLE-bench","tr":"75 Kaggle görevi; MLE-bench değerlendirmesi"},"id":"reported-result-1","methodology":{"ar":"القيم من تجارب المعيار التي حددتها الورقة؛ وليست قياسات ميدانية أو ضمانات أداء عامة.","de":"Die Werte stammen aus den im Artikel beschriebenen Benchmark-Experimenten; sie sind weder Feldmessungen noch allgemeine Leistungsgarantien.","en":"Values come from the paper's stated benchmark experiments; they are not field measurements or general performance guarantees.","es":"Las cifras proceden de los experimentos de benchmark descritos en el artículo; no son mediciones de campo ni una garantía general de rendimiento.","fr":"Les valeurs proviennent des expériences de benchmark décrites dans l’article; elles ne constituent ni des mesures de terrain ni une garantie générale de performance.","pt":"Os valores vêm dos experimentos de benchmark descritos no artigo; não são medições de campo nem garantias gerais de desempenho.","tr":"Rakamlar makalenin tanımladığı kıyaslama deneylerine aittir; saha ölçümü veya genel performans garantisi değildir."},"rowTranslations":[{"metric":{"ar":"معدل الفوز بأي ميدالية في مهام Kaggle ضمن MLE-bench","de":"Any-Medal-Rate bei Kaggle-Aufgaben in MLE-bench","en":"Any-medal rate on MLE-bench Kaggle tasks","es":"Tasa de obtención de alguna medalla en tareas Kaggle de MLE-bench","fr":"Taux de médaille obtenue sur les tâches Kaggle de MLE-bench","pt":"Taxa de obtenção de alguma medalha em tarefas Kaggle do MLE-bench","tr":"MLE-bench Kaggle görevlerinde herhangi madalya oranı"},"scope":{"ar":"75 مهمة Kaggle؛ تقييم MLE-bench","de":"75 Kaggle-Aufgaben; MLE-bench-Auswertung","en":"75 Kaggle tasks; MLE-bench evaluation","es":"75 tareas de Kaggle; evaluación MLE-bench","fr":"75 tâches Kaggle; évaluation MLE-bench","pt":"75 tarefas do Kaggle; avaliação MLE-bench","tr":"75 Kaggle görevi; MLE-bench değerlendirmesi"}}],"rows":[{"metric":"Any-medal rate on MLE-bench Kaggle tasks","scope":"75 Kaggle tasks; MLE-bench evaluation","value":78.2}],"sourceUrls":["https://arxiv.org/html/2610.13494v1"],"title":{"ar":"المقياس","de":"Messgröße","en":"Measure","es":"Medida","fr":"Mesure","pt":"Medida","tr":"Ölçüt"},"type":"table","updatedAt":"2026-10-13T00:12:48Z"},{"columns":[{"key":"metric","label":{"ar":"المقياس","de":"Messgröße","en":"Measure","es":"Medida","fr":"Mesure","pt":"Medida","tr":"Ölçüt"},"language":"en","type":"text"},{"key":"value","label":{"ar":"القيمة المعلنة","de":"Berichteter Wert","en":"Reported value","es":"Valor comunicado","fr":"Valeur rapportée","pt":"Valor informado","tr":"Bildirilen değer"},"type":"number","unit":"count"},{"key":"scope","label":{"ar":"نطاق التجربة","de":"Versuchsumfang","en":"Experimental scope","es":"Alcance experimental","fr":"Périmètre expérimental","pt":"Escopo experimental","tr":"Deney kapsamı"},"language":"en","type":"text"}],"description":{"ar":"مجموعة مهام Kaggle المذكورة في تقييم MLE-bench","de":"Im MLE-bench-Test ausgewerteter Kaggle-Aufgabensatz","en":"Kaggle task set reported in the MLE-bench evaluation","es":"Conjunto de tareas Kaggle informado en la evaluación MLE-bench","fr":"Ensemble de tâches Kaggle indiqué dans l’évaluation MLE-bench","pt":"Conjunto de tarefas Kaggle informado na avaliação do MLE-bench","tr":"MLE-bench değerlendirmesinde raporlanan Kaggle görev kümesi"},"id":"result-75","methodology":{"ar":"القيم من تجارب المعيار التي حددتها الورقة؛ وليست قياسات ميدانية أو ضمانات أداء عامة.","de":"Die Werte stammen aus den im Artikel beschriebenen Benchmark-Experimenten; sie sind weder Feldmessungen noch allgemeine Leistungsgarantien.","en":"Values come from the paper's stated benchmark experiments; they are not field measurements or general performance guarantees.","es":"Las cifras proceden de los experimentos de benchmark descritos en el artículo; no son mediciones de campo ni una garantía general de rendimiento.","fr":"Les valeurs proviennent des expériences de benchmark décrites dans l’article; elles ne constituent ni des mesures de terrain ni une garantie générale de performance.","pt":"Os valores vêm dos experimentos de benchmark descritos no artigo; não são medições de campo nem garantias gerais de desempenho.","tr":"Rakamlar makalenin tanımladığı kıyaslama deneylerine aittir; saha ölçümü veya genel performans garantisi değildir."},"rowTranslations":[{"metric":{"ar":"عدد مهام Kaggle في MLE-bench","de":"Zahl der Kaggle-Aufgaben in MLE-bench","en":"Number of MLE-bench Kaggle tasks","es":"Número de tareas Kaggle de MLE-bench","fr":"Nombre de tâches Kaggle de MLE-bench","pt":"Número de tarefas Kaggle do MLE-bench","tr":"MLE-bench Kaggle görev sayısı"},"scope":{"ar":"مجموعة مهام Kaggle المذكورة في تقييم MLE-bench","de":"Im MLE-bench-Test ausgewerteter Kaggle-Aufgabensatz","en":"Kaggle task set reported in the MLE-bench evaluation","es":"Conjunto de tareas Kaggle informado en la evaluación MLE-bench","fr":"Ensemble de tâches Kaggle indiqué dans l’évaluation MLE-bench","pt":"Conjunto de tarefas Kaggle informado na avaliação do MLE-bench","tr":"MLE-bench değerlendirmesinde raporlanan Kaggle görev kümesi"}}],"rows":[{"metric":"Number of MLE-bench Kaggle tasks","scope":"Kaggle task set reported in the MLE-bench evaluation","value":75}],"sourceUrls":["https://arxiv.org/html/2610.13494v1"],"title":{"ar":"المقياس","de":"Messgröße","en":"Measure","es":"Medida","fr":"Mesure","pt":"Medida","tr":"Ölçüt"},"type":"table","updatedAt":"2026-10-13T00:12:48Z"}],"version":1},"data_downloads":[{"formats":{"csv":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering/data/reported-result-1?lang=es&format=csv","json":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering/data/reported-result-1?lang=es&format=json"},"id":"reported-result-1"},{"formats":{"csv":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering/data/result-75?lang=es&format=csv","json":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering/data/result-75?lang=es&format=json"},"id":"result-75"}],"data_types":["table"],"editorial_illustration":{"alt":"Ilustración conceptual de tecnología, procesadores e información conectada.","asset_id":"newsverum-v1-technology","avif_variants":[{"height":320,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-480.avif","width":480},{"height":480,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-720.avif","width":720},{"height":640,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-960.avif","width":960},{"height":800,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1200.avif","width":1200},{"height":1024,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.avif","width":1536}],"credit":"Newsverum","documentary":false,"height":1024,"kind":"symbolic-editorial-illustration","language":"es","scope":"topic","url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.webp","variants":[{"height":320,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-480.webp","width":480},{"height":640,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-960.webp","width":960},{"height":1024,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.webp","width":1536}],"width":1536},"event_id":"event-5feb6b74-59c2-5e3f-984a-af92c529aa84","event_period":"2026-10-09","event_period_basis":"event-or-reference-period","id":"multi-agent-session-alternation-tests-machine-learning-engineering","image":null,"importance":0.6,"language":"es","modified_at":"2026-10-13T00:51:41+00:00","publication_basis":"publication-record","published_at":"2026-10-13T00:51:41+00:00","reading_minutes":1,"region":"world","section_illustration":{"alt":"Ilustración conceptual de tecnología, procesadores e información conectada.","asset_id":"newsverum-v1-technology","avif_variants":[{"height":320,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-480.avif","width":480},{"height":480,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-720.avif","width":720},{"height":640,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-960.avif","width":960},{"height":800,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1200.avif","width":1200},{"height":1024,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.avif","width":1536}],"credit":"Newsverum","documentary":false,"height":1024,"kind":"symbolic-editorial-illustration","language":"es","scope":"section","url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.webp","variants":[{"height":320,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-480.webp","width":480},{"height":640,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-960.webp","width":960},{"height":1024,"url":"https://newsverum.com/assets/newsverum/illustrations/v1/technology-1536.webp","width":1536}],"width":1536},"slug":"multi-agent-session-alternation-tests-machine-learning-engineering","sources":[{"checkedAt":"2026-10-13","name":"arXiv preprint by Tsinghua University, Zhejiang University and collaborating researchers","publishedAt":"2026-10-09","url":"https://arxiv.org/html/2610.13494v1"}],"summary":"Humanize MLE Agents alterna dos agentes, reinicia el contexto de cada sesión y conserva un espacio de trabajo compartido.","text":"Humanize MLE Agents alterna dos agentes, reinicia el contexto de cada sesión y conserva un espacio de trabajo compartido.\n\nInvestigadores vinculados a Tsinghua, Zhejiang y NVIDIA presentaron Humanize MLE Agents, un método que alterna las sesiones de dos agentes en tareas largas de ingeniería de aprendizaje automático. Cada sesión se detiene tras un número limitado de experimentos; el contexto se reinicia entre sesiones, mientras el código, los modelos y los resultados anteriores permanecen en un espacio de trabajo común.\n\nEn 75 tareas de Kaggle de MLE-bench, los autores informan de una tasa del 78,2 % de obtención de alguna medalla y afirman que el flujo superó la mejor referencia de código abierto con menor presupuesto de tiempo. Es un resultado de ese conjunto de concursos y esas configuraciones de agentes; no garantiza la misma mejora en otras versiones de modelos ni en proyectos reales.","title":"Investigadores alternan sesiones de agentes en tareas de aprendizaje automático","topics":[],"translations":[{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=tr","language":"tr","url":"https://newsverum.com/tr/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=en","language":"en","url":"https://newsverum.com/en/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=ar","language":"ar","url":"https://newsverum.com/ar/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=fr","language":"fr","url":"https://newsverum.com/fr/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=es","language":"es","url":"https://newsverum.com/es/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=de","language":"de","url":"https://newsverum.com/de/news/multi-agent-session-alternation-tests-machine-learning-engineering"},{"api_url":"https://newsverum.com/api/v1/articles/multi-agent-session-alternation-tests-machine-learning-engineering?lang=pt","language":"pt","url":"https://newsverum.com/pt/news/multi-agent-session-alternation-tests-machine-learning-engineering"}],"url":"https://newsverum.com/es/news/multi-agent-session-alternation-tests-machine-learning-engineering"},"version":"1"}
