Кто это
Участий в рейтингах про саму компанию — 5. За последний год у компании 27 поводов со ссылкой на источник. Чего мы про компанию не знаем: Чем занимается компания, История.
за фразой источник
наш вывод
чего не знаем
поправить
Реквизиты
Реквизитов, кроме ИНН, у нас нетКомпания не проходила сверку с государственным реестром.
поправить или дополнить
Поводы для звонка
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Automated Summarization of Financial News Using Large Language Models and Retrieval-Augmented Generation: An Early Empirical Study (Fall 2023)
arXiv:2608.19526v1 Announce Type: new Abstract: Stock market analysts and investors face a daily challenge: too much financial news, too little time. Manually reading and synthesizing hundreds of company-specific articles is impractical, yet missing key information can directly…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Learning piecewise-smooth dynamical systems
arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine learning have led to strong progress in data-driven system identification, much…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Bootstrap Theory of Representational Emergence (TBER): Explanatory Insufficiency, Transition Regimes, and the Emergence of New Representational Levels
arXiv:2606.07303v4 Announce Type: replace Abstract: Representation learning is central to modern machine learning, yet most research focuses on optimizing representations after a framework has been selected. The Bootstrap Theory of Representational Emergence (TBER) addresses a…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City
arXiv:2608.20026v1 Announce Type: cross Abstract: Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute city, where walkability and public-space quality are increasingly recognized…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Towards Clinically Faithful Medical Image Captioning via Enhanced Vision-Language Alignment
arXiv:2608.19825v1 Announce Type: cross Abstract: Medical image captioning is a technique that accelerates early-stage diagnostic workflows and enhances the interpretability of medical diagnostic AI systems. However, unlike general image captioning, clinically reliable…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries
arXiv:2608.19875v1 Announce Type: new Abstract: Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropriate response. Although these queries may be linguistically clear, they can…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Represented but Ignored: A Causal Account of Prosodic Underuse in Audio-Language Models
arXiv:2608.19211v1 Announce Type: new Abstract: Human speech is richly expressive, with prosody carrying linguistic and emotional information beyond the lexical content. A capable large audio-language model (audio-LLM) should therefore support expressive speech understanding…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use
arXiv:2608.20202v1 Announce Type: cross Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing memory benchmarks mainly evaluate whether information is correctly…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Online Test-Time Adaptation for Generalizable Dynamic Graph Anomaly Detection
arXiv:2608.19858v1 Announce Type: new Abstract: Generalizable dynamic graph anomaly detection (DGAD) enables pretrained detectors to identify anomalies in unseen target domains without costly retraining. However, existing methods often fail for two reasons. First, they mainly…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning
arXiv:2608.19447v1 Announce Type: new Abstract: Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal losses. While these events are disclosed as discrete records through news…
источник: arXiv cs.LG, 21 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning
arXiv:2608.18361v1 Announce Type: new Abstract: Figurative language is deeply culturally embedded; fluent use requires not just linguistic competence but cultural immersion. We ask whether LLMs can learn this link: does fine-tuning on cultural data improve figurative language…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science
arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leaving calculation process unobserved. Here we introduce AtmosCoder-Bench, an…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Assessing Quality of Experience in Natural Language Generation of German Text
arXiv:2608.18888v1 Announce Type: new Abstract: The rapid advancement of Natural Language Generation (NLG) has made the reliable evaluation of generated text increasingly critical, as these systems, such as large language models (LLMs), are now widely deployed in real-world…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation
arXiv:2508.13068v2 Announce Type: replace-cross Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address this gap with a two-stage multimodal framework for chest X-ray…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
arXiv:2608.18774v1 Announce Type: cross Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical limitations: reliance on only one modality for diagnosis and systematic…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Quantum-Logic Tsetlin Machines: Interpretable Quantum Machine Learning with Commuting Projector Clauses
arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which replaces Boolean literals with quantum propositions represented by projectors…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law
arXiv:2605.30497v2 Announce Type: replace Abstract: RAG-based legal assistants have been growing in popularity, but LLM hallucinations remain a key issue and potentially undermines justice. While benchmarks have been developed to evaluate progress, many rely on synthetic…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding
arXiv:2605.09874v2 Announce Type: replace-cross Abstract: Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of continuous visual experience. In ultra-long videos, relevant…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
GreekBarRetrieval: A Benchmark for Greek Statutory Retrieval
arXiv:2608.18752v2 Announce Type: cross Abstract: Statutory retrieval is necessary for citation-grounded legal question answering, but remains underexplored for Greek. We introduce GreekBarRetrieval, a public retrieval benchmark derived from, and complementing GreekBarBench…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Selection, Recombination, or a Fresh Solve? A Candidate-Free Control for Single-Pass Test-Time Aggregation
arXiv:2608.18379v1 Announce Type: new Abstract: When every candidate is wrong, correct-candidate selection is unavailable, yet the aggregation call can still solve the problem afresh. A correct aggregate answer may therefore reflect recombination, fresh solving, or both. For…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Scalable Geospatial Machine Learning for Power-Line Asset Risk: Integrating Remote Sensing for Lightning and Vegetation Risk Modelling
arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for effective intervention planning. This study contributes a modular, robust…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Online Bipartite Matching with Reusable Capacity under Non-Stationary Rewards
arXiv:2608.18130v1 Announce Type: cross Abstract: We study online bipartite matching with reusable server capacity and non-stationary rewards. Jobs arrive sequentially, reveal compatible servers, reward rates, and processing durations, and must be accepted or rejected…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
WorldPack: Dynamic Frame Compression for Long-context Video World Modeling
arXiv:2512.02473v3 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations and navigation actions. However, achieving temporally and…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
MemFuse: Multi-Source Memory Fusion from Fragmented Observations
arXiv:2608.18704v1 Announce Type: cross Abstract: Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on single-source textual histories. In realistic settings, however, relevant…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering
arXiv:2608.19029v1 Announce Type: new Abstract: Accurate and responsible medical question answering (QA) is important in healthcare, where complex cases require factual knowledge and nuanced reasoning. Existing medical QA systems, typically based on single-agent architectures…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
Mechanistic Interpretability of Structure-Aware Numerical Reasoning in LLaMA 3.1 8B
arXiv:2608.18419v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series prediction. While LLMs display in-context learning capabilities, the mechanisms with…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Публичный инфоповод — лёгкий вход в разговор без «холода»
ChatGPT search now uses the site:operator at scale
ChatGPT search now uses the site:operator at scale Promptwatch is part of the emerging "GEO" space, for Generative Engine Optimization - the chatbot version of SEO, where companies offer tools and consulting to help your site increase its presence in replies to prompts inside…
источник: Simon Willison, 20 августа 2026
поправить
Руководство
Руководство неизвестно
В открытых публикациях, которые мы разобрали, назначений по этой
компании не было.
поправить
Рейтинги и награды
| Место | Рейтинг | Издатель | Год |
|---|---|---|---|
| 39 | Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Медицина» — 2026 | Рейтинг Рунета | 2026 |
| 102 | Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Строительство и ремонт» 2026 | Рейтинг Рунета | 2026 |
| 134 | Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Торговля» — 2026 | Рейтинг Рунета | 2026 |
| 36 | Ruward: Рейтинг: Контент-маркетинг в digital-среде: 2025 | Ruward | 2025 |
| 49 | Ruward: Рейтинг: Customer Development и UX (user experience) проектирование: 2025 | Ruward | 2025 |
поправить
Вакансии
| Должность | Город | Опубликована |
|---|---|---|
| Контент-редактор | Самара | 20 июля 2026 |
Хроника
Новость
2 дн. назад
2 дн. назад
Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning
arXiv:2608.19447v1 Announce Type: new Abstract: Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal losses. While these events are disclosed as discrete records through news…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Online Test-Time Adaptation for Generalizable Dynamic Graph Anomaly Detection
arXiv:2608.19858v1 Announce Type: new Abstract: Generalizable dynamic graph anomaly detection (DGAD) enables pretrained detectors to identify anomalies in unseen target domains without costly retraining. However, existing methods often fail for two reasons. First, they mainly…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use
arXiv:2608.20202v1 Announce Type: cross Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing memory benchmarks mainly evaluate whether information is correctly…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Represented but Ignored: A Causal Account of Prosodic Underuse in Audio-Language Models
arXiv:2608.19211v1 Announce Type: new Abstract: Human speech is richly expressive, with prosody carrying linguistic and emotional information beyond the lexical content. A capable large audio-language model (audio-LLM) should therefore support expressive speech understanding…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries
arXiv:2608.19875v1 Announce Type: new Abstract: Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropriate response. Although these queries may be linguistically clear, they can…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Towards Clinically Faithful Medical Image Captioning via Enhanced Vision-Language Alignment
arXiv:2608.19825v1 Announce Type: cross Abstract: Medical image captioning is a technique that accelerates early-stage diagnostic workflows and enhances the interpretability of medical diagnostic AI systems. However, unlike general image captioning, clinically reliable…
источник: arXiv cs.CL, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City
arXiv:2608.20026v1 Announce Type: cross Abstract: Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute city, where walkability and public-space quality are increasingly recognized…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Bootstrap Theory of Representational Emergence (TBER): Explanatory Insufficiency, Transition Regimes, and the Emergence of New Representational Levels
arXiv:2606.07303v4 Announce Type: replace Abstract: Representation learning is central to modern machine learning, yet most research focuses on optimizing representations after a framework has been selected. The Bootstrap Theory of Representational Emergence (TBER) addresses a…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Learning piecewise-smooth dynamical systems
arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine learning have led to strong progress in data-driven system identification, much…
источник: arXiv cs.LG, 21 августа 2026
Новость
2 дн. назад
2 дн. назад
Automated Summarization of Financial News Using Large Language Models and Retrieval-Augmented Generation: An Early Empirical Study (Fall 2023)
arXiv:2608.19526v1 Announce Type: new Abstract: Stock market analysts and investors face a daily challenge: too much financial news, too little time. Manually reading and synthesizing hundreds of company-specific articles is impractical, yet missing key information can directly…
источник: arXiv cs.CL, 21 августа 2026
Новость
3 дн. назад
3 дн. назад
ChatGPT search now uses the site:operator at scale
ChatGPT search now uses the site:operator at scale Promptwatch is part of the emerging "GEO" space, for Generative Engine Optimization - the chatbot version of SEO, where companies offer tools and consulting to help your site increase its presence in replies to prompts inside…
источник: Simon Willison, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Mechanistic Interpretability of Structure-Aware Numerical Reasoning in LLaMA 3.1 8B
arXiv:2608.18419v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series prediction. While LLMs display in-context learning capabilities, the mechanisms with…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering
arXiv:2608.19029v1 Announce Type: new Abstract: Accurate and responsible medical question answering (QA) is important in healthcare, where complex cases require factual knowledge and nuanced reasoning. Existing medical QA systems, typically based on single-agent architectures…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
MemFuse: Multi-Source Memory Fusion from Fragmented Observations
arXiv:2608.18704v1 Announce Type: cross Abstract: Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on single-source textual histories. In realistic settings, however, relevant…
источник: arXiv cs.AI, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
WorldPack: Dynamic Frame Compression for Long-context Video World Modeling
arXiv:2512.02473v3 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on past observations and navigation actions. However, achieving temporally and…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Online Bipartite Matching with Reusable Capacity under Non-Stationary Rewards
arXiv:2608.18130v1 Announce Type: cross Abstract: We study online bipartite matching with reusable server capacity and non-stationary rewards. Jobs arrive sequentially, reveal compatible servers, reward rates, and processing durations, and must be accepted or rejected…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Scalable Geospatial Machine Learning for Power-Line Asset Risk: Integrating Remote Sensing for Lightning and Vegetation Risk Modelling
arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for effective intervention planning. This study contributes a modular, robust…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Selection, Recombination, or a Fresh Solve? A Candidate-Free Control for Single-Pass Test-Time Aggregation
arXiv:2608.18379v1 Announce Type: new Abstract: When every candidate is wrong, correct-candidate selection is unavailable, yet the aggregation call can still solve the problem afresh. A correct aggregate answer may therefore reflect recombination, fresh solving, or both. For…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
GreekBarRetrieval: A Benchmark for Greek Statutory Retrieval
arXiv:2608.18752v2 Announce Type: cross Abstract: Statutory retrieval is necessary for citation-grounded legal question answering, but remains underexplored for Greek. We introduce GreekBarRetrieval, a public retrieval benchmark derived from, and complementing GreekBarBench…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding
arXiv:2605.09874v2 Announce Type: replace-cross Abstract: Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of continuous visual experience. In ultra-long videos, relevant…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law
arXiv:2605.30497v2 Announce Type: replace Abstract: RAG-based legal assistants have been growing in popularity, but LLM hallucinations remain a key issue and potentially undermines justice. While benchmarks have been developed to evaluate progress, many rely on synthetic…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Quantum-Logic Tsetlin Machines: Interpretable Quantum Machine Learning with Commuting Projector Clauses
arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which replaces Boolean literals with quantum propositions represented by projectors…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification
arXiv:2608.18774v1 Announce Type: cross Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical limitations: reliance on only one modality for diagnosis and systematic…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation
arXiv:2508.13068v2 Announce Type: replace-cross Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address this gap with a two-stage multimodal framework for chest X-ray…
источник: arXiv cs.LG, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Assessing Quality of Experience in Natural Language Generation of German Text
arXiv:2608.18888v1 Announce Type: new Abstract: The rapid advancement of Natural Language Generation (NLG) has made the reliable evaluation of generated text increasingly critical, as these systems, such as large language models (LLMs), are now widely deployed in real-world…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science
arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leaving calculation process unobserved. Here we introduce AtmosCoder-Bench, an…
источник: arXiv cs.CL, 20 августа 2026
Новость
3 дн. назад
3 дн. назад
Figurative and Cultural Knowledge in LLMs: Investigating Cross-Domain Transfer through Fine-Tuning
arXiv:2608.18361v1 Announce Type: new Abstract: Figurative language is deeply culturally embedded; fluent use requires not just linguistic competence but cultural immersion. We ask whether LLMs can learn this link: does fine-tuning on cultural data improve figurative language…
источник: arXiv cs.CL, 20 августа 2026
Вакансия
1 мес. назад
1 мес. назад
Рейтинг
1 мес. назад
1 мес. назад
102 место в рейтинге «Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Строительство и ремонт» 2026»
Рейтинг Рунета, 2026.
источник: Рейтинг Рунета, 1 июля 2026
Рейтинг
1 мес. назад
1 мес. назад
134 место в рейтинге «Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Торговля» — 2026»
Рейтинг Рунета, 2026.
источник: Рейтинг Рунета, 1 июля 2026
Рейтинг
1 мес. назад
1 мес. назад
39 место в рейтинге «Рейтинг Рунета: Рейтинг «Подрядчики с экспертизой в отрасли Медицина» — 2026»
Рейтинг Рунета, 2026.
источник: Рейтинг Рунета, 1 июля 2026
Рейтинг
1 июля 2025
1 июля 2025
36 место в рейтинге «Ruward: Рейтинг: Контент-маркетинг в digital-среде: 2025»
Ruward, 2025.
источник: Ruward, 1 июля 2025
Рейтинг
1 июля 2025
1 июля 2025
49 место в рейтинге «Ruward: Рейтинг: Customer Development и UX (user experience) проектирование: 2025»
Ruward, 2025.
источник: Ruward, 1 июля 2025
Чего мы про компанию не знаем
Этих разделов нет ни у одной компании в справочнике: таких источников у нас пока нет вовсе. Знаете — расскажите, и на странице появится то, что вы написали, а не наш пересказ.
Чем занимается компания
поправить или дополнить
История