https://chiosa.app/papers/accelerating-so-2-equivariant-materials-models-through-low-precision-emulation-2610-35164Chiosaen2026-10-27T09:16:52ZFlashSO(2) speeds symmetry-preserving layers with integer emulationhttps://chiosa.app/papers/adapt-for-planning-not-just-prediction-optimistic-test-time-world-model-adaptation-2610-35636Chiosaen2026-10-27T09:16:52ZPlanning-aware updates help world models adapt to shiftshttps://chiosa.app/papers/adapt-for-planning-not-just-prediction-optimistic-test-time-world-model-adaptation-2610-35636?lang=frChiosafr2026-10-27T09:16:52ZDes mises à jour guidées par la planification aident les modèles du monde à s’adapter aux changementshttps://chiosa.app/papers/audit-where-hacks-pay-budgeted-strong-verifier-audits-against-reward-hacking-in-grpo-2610-35716Chiosaen2026-10-27T09:16:52ZTargeted audits nearly eliminate coding reward hackinghttps://chiosa.app/papers/audit-where-hacks-pay-budgeted-strong-verifier-audits-against-reward-hacking-in-grpo-2610-35716?lang=esChiosaes2026-10-27T09:16:52ZAuditorías dirigidas casi eliminan las trampas de recompensa en programaciónhttps://chiosa.app/papers/back-to-basics-a-skill-centric-approach-to-generalist-web-agents-2610-35823Chiosaen2026-10-27T09:16:52ZA planner helps browser agents use practiced web skillshttps://chiosa.app/papers/back-to-basics-a-skill-centric-approach-to-generalist-web-agents-2610-35823?lang=itChiosait2026-10-27T09:16:52ZUn planner aiuta gli agenti browser a usare abilità web esercitatehttps://chiosa.app/papers/back-to-basics-a-skill-centric-approach-to-generalist-web-agents-2610-35823?lang=esChiosaes2026-10-27T09:16:52ZUn planificador ayuda a los agentes a usar habilidades web practicadashttps://chiosa.app/papers/back-to-basics-a-skill-centric-approach-to-generalist-web-agents-2610-35823?lang=frChiosafr2026-10-27T09:16:52ZUn planificateur aide les agents de navigation à mobiliser leurs compétences webhttps://chiosa.app/papers/built-to-remember-shipped-to-forget-operational-contracts-failures-and-repairs-in-containerized-llm-agent-dep-2610-34620Chiosaen2026-10-27T09:16:52ZFourteen deployment guarantees expose risks to agent systemshttps://chiosa.app/papers/constrained-decoding-harmful-or-beneficial-revisiting-its-impact-on-llm-performance-2610-35328Chiosaen2026-10-27T09:16:52ZMatched tests find constrained decoding need not hurt accuracyhttps://chiosa.app/papers/constrained-decoding-harmful-or-beneficial-revisiting-its-impact-on-llm-performance-2610-35328?lang=itChiosait2026-10-27T09:16:52ZTest abbinati: il decoding vincolato non riduce necessariamente l’accuratezzahttps://chiosa.app/papers/constrained-decoding-harmful-or-beneficial-revisiting-its-impact-on-llm-performance-2610-35328?lang=esChiosaes2026-10-27T09:16:52ZLas pruebas controladas muestran que la decodificación restringida no tiene por qué reducir la precisiónhttps://chiosa.app/papers/constrained-decoding-harmful-or-beneficial-revisiting-its-impact-on-llm-performance-2610-35328?lang=frChiosafr2026-10-27T09:16:52ZDes tests contrôlés montrent que le décodage contraint ne nuit pas forcément à la précisionhttps://chiosa.app/papers/cosa-the-conflict-of-skills-attack-in-real-world-llm-agent-ecosystems-2610-35082Chiosaen2026-10-27T09:16:52ZChecked Skills can still combine into policy violationshttps://chiosa.app/papers/discodemo-discovering-efficient-and-diverse-robot-demonstrations-for-imitation-learning-2610-32093Chiosaen2026-10-27T09:16:52ZDiverse robot demonstrations improve imitation learninghttps://chiosa.app/papers/dynaflow-learning-free-form-multi-agent-orchestration-2610-34467Chiosaen2026-10-27T09:16:52ZDynaFlow: Learning free-form multi-agent orchestrationhttps://chiosa.app/papers/efficient-probabilistic-weather-forecasting-at-quarter-degree-resolution-with-two-sided-transport-attention-2610-35545Chiosaen2026-10-27T09:16:52ZA weather model brings detail to global forecastshttps://chiosa.app/papers/efficient-probabilistic-weather-forecasting-at-quarter-degree-resolution-with-two-sided-transport-attention-2610-35545?lang=itChiosait2026-10-27T09:16:52ZUn modello meteorologico porta più dettaglio nelle previsioni globalihttps://chiosa.app/papers/efficient-probabilistic-weather-forecasting-at-quarter-degree-resolution-with-two-sided-transport-attention-2610-35545?lang=esChiosaes2026-10-27T09:16:52ZUn modelo meteorológico detalla los pronósticos globaleshttps://chiosa.app/papers/excise-locating-and-excising-distracting-sentences-in-medical-question-answering-2610-35558Chiosaen2026-10-27T09:16:52ZA sentence-level method reduces targeted distraction in medical QAhttps://chiosa.app/papers/excise-locating-and-excising-distracting-sentences-in-medical-question-answering-2610-35558?lang=itChiosait2026-10-27T09:16:52ZUn metodo per ridurre le distrazioni mirate nelle domande medichehttps://chiosa.app/papers/excise-locating-and-excising-distracting-sentences-in-medical-question-answering-2610-35558?lang=esChiosaes2026-10-27T09:16:52ZUn método por oración reduce las distracciones dirigidas en preguntas médicashttps://chiosa.app/papers/excise-locating-and-excising-distracting-sentences-in-medical-question-answering-2610-35558?lang=frChiosafr2026-10-27T09:16:52ZUne méthode phrase par phrase réduit les distractions ciblées en questions médicaleshttps://chiosa.app/papers/governing-enterprise-ai-traffic-at-scale-design-and-operation-of-a-policy-driven-multi-vendor-llm-gateway-on-2610-35509Chiosaen2026-10-27T09:16:52ZPayPal’s gateway brings multi-vendor AI access under shared ruleshttps://chiosa.app/papers/governing-enterprise-ai-traffic-at-scale-design-and-operation-of-a-policy-driven-multi-vendor-llm-gateway-on-2610-35509?lang=frChiosafr2026-10-27T09:16:52ZLa passerelle de PayPal unifie l’accès à plusieurs fournisseurs d’IA sous des règles communeshttps://chiosa.app/papers/hilo-towards-product-level-graceful-degradation-with-a-quality-aware-load-aware-control-framework-2610-34844Chiosaen2026-10-27T09:16:52ZHiLO coordinates service slowdowns to protect product qualityhttps://chiosa.app/papers/identities-not-pairs-distribution-free-false-accept-control-for-embedding-based-verification-2610-35277Chiosaen2026-10-27T09:16:52ZA trial-aware image test controls false matcheshttps://chiosa.app/papers/identities-not-pairs-distribution-free-false-accept-control-for-embedding-based-verification-2610-35277?lang=itChiosait2026-10-27T09:16:52ZUn test delle immagini tiene conto della prova per controllare i falsi matchhttps://chiosa.app/papers/imagetts-repurposing-pretrained-image-diffusion-transformers-for-speech-synthesis-2610-34807Chiosaen2026-10-27T09:16:52ZImage-generation models can help a speech system learn wordshttps://chiosa.app/papers/interactiveworld-a-verifiable-human-centric-environment-for-building-better-interactive-mllm-assistants-2610-33966Chiosaen2026-10-27T09:16:52ZA simulator tests assistants as advice changes eventshttps://chiosa.app/papers/octen-webgr-scaling-generative-retrieval-to-200-million-web-pages-2610-35256Chiosaen2026-10-27T09:16:52ZA language model ranks pages from search clickshttps://chiosa.app/papers/one-megakernel-is-not-enough-predicting-where-to-cut-for-streaming-inference-2610-35336Chiosaen2026-10-27T09:16:52ZA planner finds where streaming models should fuse GPU workhttps://chiosa.app/papers/one-megakernel-is-not-enough-predicting-where-to-cut-for-streaming-inference-2610-35336?lang=esChiosaes2026-10-27T09:16:52ZUn planificador decide dónde fusionar el trabajo en la GPUhttps://chiosa.app/papers/silent-and-costly-characterizing-and-detecting-prompt-caching-mis-integration-in-llm-agents-2610-34817Chiosaen2026-10-27T09:16:52ZA code checker finds silent prompt-caching defectshttps://chiosa.app/papers/streamvibe-proactive-video-agents-for-evolving-user-intent-2610-34662Chiosaen2026-10-27T09:16:52ZA video agent tracks changing goals to time its helphttps://chiosa.app/papers/the-hidden-costs-of-forgetting-a-study-of-trajectory-deletion-in-software-engineering-agents-2610-35496Chiosaen2026-10-27T09:16:52ZDeleting agent history works best when recent tool results stayhttps://chiosa.app/papers/the-hidden-costs-of-forgetting-a-study-of-trajectory-deletion-in-software-engineering-agents-2610-35496?lang=esChiosaes2026-10-27T09:16:52ZLos agentes resuelven mejor las tareas si conservan los resultados recientes de las herramientashttps://chiosa.app/papers/the-price-of-scale-in-proactive-memory-recall-2610-34507Chiosaen2026-10-27T09:16:52ZWhy fixed thresholds can fail as memory stores growhttps://chiosa.app/papers/the-voice-on-the-line-2610-35272Chiosaen2026-10-27T09:16:52ZVoice isolation improves overlap, but still harms lone callershttps://chiosa.app/papers/the-voice-on-the-line-2610-35272?lang=itChiosait2026-10-27T09:16:52ZL’isolamento vocale migliora con voci sovrapposte, ma danneggia ancora chi parla da solohttps://chiosa.app/papers/trajectory2gym-decision-grounded-compositional-interaction-synthesis-for-tool-use-agents-2610-33568Chiosaen2026-10-27T09:16:52ZA method builds grounded tool-use training interactionshttps://chiosa.app/papers/what-effort-level-should-i-choose-on-the-economics-of-reasoning-effort-in-llm-agents-2610-34491Chiosaen2026-10-27T09:16:52ZHigher reasoning effort can miss cheaper successeshttps://chiosa.app/papers/world-in-context-interactive-video-world-modeling-with-in-context-conditioning-2610-33169Chiosaen2026-10-27T09:16:52ZExplicit view controls help video models separate motion and switch viewshttps://chiosa.app/papers/accordion-elastic-depth-inference-via-fixed-prefix-layer-looping-2610-32492Chiosaen2026-10-26T20:35:07ZOne Transformer serves five compute budgets with shared weightshttps://chiosa.app/papers/accordion-elastic-depth-inference-via-fixed-prefix-layer-looping-2610-32492?lang=itChiosait2026-10-26T20:35:07ZUn Transformer offre cinque budget di calcolo con pesi condivisihttps://chiosa.app/papers/accordion-elastic-depth-inference-via-fixed-prefix-layer-looping-2610-32492?lang=frChiosafr2026-10-26T20:35:07ZUn Transformer propose cinq budgets de calcul avec des poids partagéshttps://chiosa.app/papers/agentic-ai-defense-decode-time-provenance-binding-for-mcp-2610-31974Chiosaen2026-10-26T20:35:07ZA decode-time defense keeps hidden instructions from critical callshttps://chiosa.app/papers/agentic-ai-defense-decode-time-provenance-binding-for-mcp-2610-31974?lang=frChiosafr2026-10-26T20:35:07ZUne défense au décodage bloque les instructions cachées avant les appels critiqueshttps://chiosa.app/papers/biloco-binary-low-rank-corrections-for-post-training-quantization-2610-32243Chiosaen2026-10-26T20:35:07ZBinary corrections match or improve quality at equal storagehttps://chiosa.app/papers/biloco-binary-low-rank-corrections-for-post-training-quantization-2610-32243?lang=itChiosait2026-10-26T20:35:07ZCorrezioni binarie: qualità pari o migliore a parità di spaziohttps://chiosa.app/papers/biloco-binary-low-rank-corrections-for-post-training-quantization-2610-32243?lang=esChiosaes2026-10-26T20:35:07ZLas correcciones binarias igualan o mejoran la calidad con el mismo almacenamientohttps://chiosa.app/papers/data-quality-in-rvl-cdip-a-systematic-audit-2610-32126Chiosaen2026-10-26T20:35:07ZRVL-CDIP scores reflect more than document recognitionhttps://chiosa.app/papers/data-quality-in-rvl-cdip-a-systematic-audit-2610-32126?lang=itChiosait2026-10-26T20:35:07ZI punteggi di RVL-CDIP misurano più del riconoscimento dei documentihttps://chiosa.app/papers/data-quality-in-rvl-cdip-a-systematic-audit-2610-32126?lang=esChiosaes2026-10-26T20:35:07ZLas puntuaciones de RVL-CDIP reflejan algo más que reconocer documentoshttps://chiosa.app/papers/detecting-insecure-compositions-of-clean-agent-skills-via-capability-flow-graph-analysis-2610-32155Chiosaen2026-10-26T20:35:07ZClean agent skills can combine into unsafe action chainshttps://chiosa.app/papers/detecting-insecure-compositions-of-clean-agent-skills-via-capability-flow-graph-analysis-2610-32155?lang=itChiosait2026-10-26T20:35:07ZSkill pulite per agenti possono formare catene di azioni insicurehttps://chiosa.app/papers/embedding-large-pqc-kems-in-ikev2-2610-32356Chiosaen2026-10-26T20:35:07ZQUIC speeds two IKEv2 key types, but huge keys still strugglehttps://chiosa.app/papers/embedding-large-pqc-kems-in-ikev2-2610-32356?lang=itChiosait2026-10-26T20:35:07ZQUIC accelera due tipi di chiave IKEv2, ma le chiavi enormi restano difficilihttps://chiosa.app/papers/embedding-large-pqc-kems-in-ikev2-2610-32356?lang=esChiosaes2026-10-26T20:35:07ZQUIC acelera dos tipos de clave en IKEv2, pero las claves enormes siguen dando problemashttps://chiosa.app/papers/forecasting-associations-not-interventions-a-preregistered-causal-audit-of-covariate-aware-time-series-founda-2610-31869Chiosaen2026-10-26T20:35:07ZWhat-if forecasts can mistake association for causal effecthttps://chiosa.app/papers/full-weight-vla-fine-tuning-without-an-fp32-master-copy-silently-erases-most-updates-2610-31859Chiosaen2026-10-26T20:35:07ZFull-precision weight copies help two robot models learn taskshttps://chiosa.app/papers/hyscale-scaling-long-context-training-for-learned-sparse-attention-2610-32057Chiosaen2026-10-26T20:35:07ZHyScale speeds up million-token training for sparse attentionhttps://chiosa.app/papers/hyscale-scaling-long-context-training-for-learned-sparse-attention-2610-32057?lang=itChiosait2026-10-26T20:35:07ZHyScale accelera l’addestramento con un milione di token per l’attenzione sparsahttps://chiosa.app/papers/hyscale-scaling-long-context-training-for-learned-sparse-attention-2610-32057?lang=esChiosaes2026-10-26T20:35:07ZHyScale acelera el entrenamiento con atención dispersa con un millón de tokenshttps://chiosa.app/papers/incomparable-minima-in-agent-tool-authorization-2610-31914Chiosaen2026-10-26T20:35:07ZPermission tables can offer several minimal grantshttps://chiosa.app/papers/knowing-when-to-stop-the-evidence-action-gap-in-coding-agents-2610-31895Chiosaen2026-10-26T20:35:07ZAn escalation option helps coding agents stop at repair barriershttps://chiosa.app/papers/kvstream-adaptive-parallel-storage-management-for-kv-caching-in-large-scale-llm-serving-2610-31827Chiosaen2026-10-26T20:35:07ZKVStream uses idle storage to speed long-context model servinghttps://chiosa.app/papers/loca-enabling-multi-modality-in-geospatial-location-encoders-2610-32894Chiosaen2026-10-26T20:35:07ZLoCA turns satellite imagery into location embeddingshttps://chiosa.app/papers/loca-enabling-multi-modality-in-geospatial-location-encoders-2610-32894?lang=itChiosait2026-10-26T20:35:07ZLoCA trasforma le immagini satellitari in embedding di localitàhttps://chiosa.app/papers/loca-enabling-multi-modality-in-geospatial-location-encoders-2610-32894?lang=frChiosafr2026-10-26T20:35:07ZLoCA transforme les images satellites en plongements de lieuxhttps://chiosa.app/papers/metadb-putting-file-system-structure-back-into-distributed-databases-2610-32247Chiosaen2026-10-26T20:35:07ZMetaDB reshapes databases around file-system metadatahttps://chiosa.app/papers/metadb-putting-file-system-structure-back-into-distributed-databases-2610-32247?lang=itChiosait2026-10-26T20:35:07ZMetaDB ripensa i database intorno ai metadati dei file systemhttps://chiosa.app/papers/metadb-putting-file-system-structure-back-into-distributed-databases-2610-32247?lang=esChiosaes2026-10-26T20:35:07ZMetaDB adapta las bases de datos a los metadatos de sistemas de archivoshttps://chiosa.app/papers/metadb-putting-file-system-structure-back-into-distributed-databases-2610-32247?lang=frChiosafr2026-10-26T20:35:07ZMetaDB repense les bases autour des métadonnées de fichiershttps://chiosa.app/papers/omni-woodpecker-hallucination-correction-via-evidence-prior-rebalancing-for-omni-llms-2610-27103Chiosaen2026-10-26T20:35:07ZA frozen multimodal model can rebalance conflicting cueshttps://chiosa.app/papers/on-task-off-track-benchmarking-llm-and-agent-robustness-to-near-target-prompt-injection-2610-32531Chiosaen2026-10-26T20:35:07ZRelated prompt attacks reveal missed failureshttps://chiosa.app/papers/on-task-off-track-benchmarking-llm-and-agent-robustness-to-near-target-prompt-injection-2610-32531?lang=esChiosaes2026-10-26T20:35:07ZAtaques relacionados revelan fallos que pasan inadvertidoshttps://chiosa.app/papers/on-task-off-track-benchmarking-llm-and-agent-robustness-to-near-target-prompt-injection-2610-32531?lang=frChiosafr2026-10-26T20:35:07ZDes attaques liées à la tâche révèlent des échecs manquéshttps://chiosa.app/papers/pairing-matters-performance-failures-and-efficiency-in-lightweight-coding-agents-2610-32131Chiosaen2026-10-26T20:35:07ZCoding-agent harness choice changes lightweight models’ resultshttps://chiosa.app/papers/pairing-matters-performance-failures-and-efficiency-in-lightweight-coding-agents-2610-32131?lang=esChiosaes2026-10-26T20:35:07ZEl harness cambia los resultados de los modelos ligeros de programaciónhttps://chiosa.app/papers/pairing-matters-performance-failures-and-efficiency-in-lightweight-coding-agents-2610-32131?lang=frChiosafr2026-10-26T20:35:07ZLe choix de l’agent modifie les résultats des modèles légers de programmationhttps://chiosa.app/papers/probing-the-limits-of-forward-screening-and-inverse-design-of-crystal-materials-2610-32678Chiosaen2026-10-26T20:35:07ZA unified crystal database changes screening and novelty claimshttps://chiosa.app/papers/probing-the-limits-of-forward-screening-and-inverse-design-of-crystal-materials-2610-32678?lang=itChiosait2026-10-26T20:35:07ZUn database cristallino integrato cambia screening e novitàhttps://chiosa.app/papers/probing-the-limits-of-forward-screening-and-inverse-design-of-crystal-materials-2610-32678?lang=esChiosaes2026-10-26T20:35:07ZUna base unificada de cristales cambia el análisis del cribado y la novedadhttps://chiosa.app/papers/probing-the-limits-of-forward-screening-and-inverse-design-of-crystal-materials-2610-32678?lang=frChiosafr2026-10-26T20:35:07ZUne base unifiée de cristaux revoit le criblage et les critères de nouveautéhttps://chiosa.app/papers/pseudo-labels-as-rewards-not-targets-group-relative-policy-optimization-for-semi-supervised-asr-2610-32572Chiosaen2026-10-26T20:35:07ZGroup scoring helps speech models avoid teacher errorshttps://chiosa.app/papers/pseudo-labels-as-rewards-not-targets-group-relative-policy-optimization-for-semi-supervised-asr-2610-32572?lang=itChiosait2026-10-26T20:35:07ZIl punteggio di gruppo aiuta i modelli vocali a evitare gli errori del teacherhttps://chiosa.app/papers/pseudo-labels-as-rewards-not-targets-group-relative-policy-optimization-for-semi-supervised-asr-2610-32572?lang=esChiosaes2026-10-26T20:35:07ZLa puntuación grupal ayuda a los modelos de voz a evitar errores del docentehttps://chiosa.app/papers/pseudo-labels-as-rewards-not-targets-group-relative-policy-optimization-for-semi-supervised-asr-2610-32572?lang=frChiosafr2026-10-26T20:35:07ZLe score par groupe aide les modèles vocaux à éviter les erreurs de leur enseignanthttps://chiosa.app/papers/rewriting-scaling-laws-for-synthetic-data-with-compute-and-data-constraints-2610-31867Chiosaen2026-10-26T20:35:07ZA formula predicts how much rewritten text to train onhttps://chiosa.app/papers/rynnunify-towards-unified-embodied-brain-2610-32965Chiosaen2026-10-26T20:35:07ZRynnUnify links video prediction with long-horizon planninghttps://chiosa.app/papers/rynnunify-towards-unified-embodied-brain-2610-32965?lang=itChiosait2026-10-26T20:35:07ZRynnUnify collega la previsione video alla pianificazione estesahttps://chiosa.app/papers/rynnunify-towards-unified-embodied-brain-2610-32965?lang=esChiosaes2026-10-26T20:35:07ZRynnUnify vincula la predicción de video con la planificación a largo plazohttps://chiosa.app/papers/rynnunify-towards-unified-embodied-brain-2610-32965?lang=frChiosafr2026-10-26T20:35:07ZRynnUnify relie prédiction vidéo et planification à long termehttps://chiosa.app/papers/sure-tagger-structured-speech-representations-for-compositional-evaluation-and-targeted-data-selection-2610-32198Chiosaen2026-10-26T20:35:07ZSURE-Tagger makes speech conditions easier to comparehttps://chiosa.app/papers/sure-tagger-structured-speech-representations-for-compositional-evaluation-and-targeted-data-selection-2610-32198?lang=itChiosait2026-10-26T20:35:07ZSURE-Tagger facilita il confronto delle condizioni vocalihttps://chiosa.app/papers/sure-tagger-structured-speech-representations-for-compositional-evaluation-and-targeted-data-selection-2610-32198?lang=esChiosaes2026-10-26T20:35:07ZSURE-Tagger facilita comparar condiciones del hablahttps://chiosa.app/papers/sure-tagger-structured-speech-representations-for-compositional-evaluation-and-targeted-data-selection-2610-32198?lang=frChiosafr2026-10-26T20:35:07ZSURE-Tagger facilite la comparaison des conditions vocaleshttps://chiosa.app/papers/tgr-evodag-a-dag-based-multi-agent-code-evolution-framework-for-generative-recommendation-on-tencent-2610-32326Chiosaen2026-10-26T20:35:07ZA search framework adapts recommendation pipelines across stageshttps://chiosa.app/papers/the-3ds-oracle-bin-attack-via-the-network-2610-32206Chiosaen2026-10-26T20:35:07Z3-D Secure lookup results can expose account signalshttps://chiosa.app/papers/the-3ds-oracle-bin-attack-via-the-network-2610-32206?lang=itChiosait2026-10-26T20:35:07ZI risultati del lookup 3-D Secure possono rivelare segnali sugli accounthttps://chiosa.app/papers/the-3ds-oracle-bin-attack-via-the-network-2610-32206?lang=esChiosaes2026-10-26T20:35:07ZLos resultados de consulta de 3-D Secure pueden revelar señales de cuentashttps://chiosa.app/papers/the-3ds-oracle-bin-attack-via-the-network-2610-32206?lang=frChiosafr2026-10-26T20:35:07ZLes résultats de requête 3-D Secure peuvent révéler des indices sur les compteshttps://chiosa.app/papers/the-llens-platform-for-on-premises-large-language-model-agents-in-a-japanese-university-hospital-development-2610-32151Chiosaen2026-10-26T20:35:07ZA hospital AI platform runs with its tools inside a closed 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