Data papers

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67 papers found

ReviewPaperPublishedTopics

7.0SpecAlign: Efficient Specification-Grounded Alignment of Large Language Models via Synthetic DataAligning LLMs with specific and evolving model specifications is crucial for ensuring compliance and adaptability in real-world applications.Sep 4, 2026LLM Alignment Data

6.8Evaluating Investment Logic in Large Language Models: A Real-World Benchmark Towards Personalzied Financial AgentsUnderstanding and improving the decision-making process of financial agents can lead to more reliable and personalized financial advice, which is crucial for investors with diverse goals and risk profiles.Aug 21, 2026LLM Agent Reasoning

6.8Small Foundation Models of Human Cognition and BehaviourUnderstanding the capabilities and limitations of smaller models in cognitive tasks can inform the development of efficient AI systems that mimic human-like reasoning and decision-making.Aug 12, 2026LLM Evaluation Data

7.2Measuring the Cross-Lingual Comprehension Gap: How the language of the evidence shapes what language models understandUnderstanding the cross-lingual comprehension gap is crucial for developing more equitable and effective language models that serve a global audience, especially for low-resource languages.Aug 10, 2026Evaluation Benchmark Data

7.2MameLoshnLM: Yiddish Language Model and Evaluation BenchmarkThis work provides a significant step forward in NLP for Yiddish, a historically rich but digitally underrepresented language, offering a template for similar efforts in other low-resource languages.Aug 8, 2026LLM Benchmark Data

6.8Formal Verification of Agentic Systems over Operational DataAs LLM-driven systems become more prevalent in operational workflows, ensuring their compliance with business logic and data integrity is crucial for reliable deployment.Aug 5, 2026LLM Agent Data

6.8Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation ModelsUnderstanding the OOD performance of TFMs is crucial for their reliable deployment in real-world applications where distribution shifts are common.Jul 29, 2026Evaluation Benchmark Data

6.8Reasoning or Memorization: Can LLMs Understand and Generate Chinese Xiehouyu Riddles?Understanding the limitations of LLMs in reasoning and creativity, especially in non-English contexts, is crucial for developing more robust and versatile AI systems.Jul 28, 2026LLM Reasoning Evaluation

7.2LunarFM: A Shared Multimodal Representation of the Moon's SurfaceLunarFM provides a comprehensive tool for lunar exploration, enabling more efficient analysis and utilization of lunar resources, which is crucial for future lunar missions and potential colonization.Jul 27, 2026Multimodal Data

7.2Atlas 2 -- Foundation models for clinical deploymentThis work is significant for AI researchers and engineers focused on healthcare, as it addresses key limitations in deploying pathology models clinically, potentially leading to more reliable and efficient diagnostic tools.Jul 27, 2026Vision Language Benchmark Data

7.5LinguistAgent Technical Report: A Reflective Multi-Model Platform for Automated Linguistic AnnotationThis research addresses a critical bottleneck in humanities and social sciences by enhancing the efficiency of linguistic annotation, which is essential for various research applications.Jul 22, 2026LLM Agent Evaluation

7.5OpenMHC: Accelerating the Science of Wearable Foundation ModelsThis work addresses the critical lack of publicly available wearable health datasets, enabling researchers to advance the field of wearable health AI more effectively.Jul 22, 2026Data Benchmark

6.5Trusting sovereign language models as scientific instruments: evidence from Portugal's AMALIAUnderstanding the limitations of national language models like AMALIA in accurately annotating complex constructs is crucial for their effective deployment in real-world applications.Jul 21, 2026LLM Evaluation Data

7.2FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series ForecastingThis research highlights the potential of foundation models to provide scalable and generalizable solutions for energy forecasting, which is crucial for efficient energy system planning and operation.Jul 21, 2026Benchmark Data

7.2Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment FrameworkThis work is significant for AI engineers and researchers interested in privacy-preserving collaborative learning across multimodal datasets, offering a method to improve model performance without compromising data privacy.Jul 20, 2026Multimodal Alignment Data

6.8The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic ReasoningUnderstanding and leveraging GeoFMs can significantly enhance the efficiency and accessibility of AI/ML in geospatial analysis, making it crucial for researchers and engineers working in this domain.Jul 15, 2026Multimodal Vision Language Agent

7.2A Foundation Model for Multimodal Event Sequences in Financial ApplicationsThis approach could streamline financial predictive modeling by leveraging diverse data sources, potentially leading to more accurate predictions and efficient model development.Jul 14, 2026Multimodal Architecture Data

7.5Efficiently Adapting Spoken Language Models for the Singaporean ContextThe study addresses the challenge of adapting language models to specific cultural and linguistic contexts, which is crucial for effective multilingual interaction in diverse environments.Jul 14, 2026LLM Data Evaluation

7.5Agentic AI and Retrieval-Augmented Models in Straight-Through UnderwritingUnderstanding how advanced AI models can enhance actuarial practices is crucial for professionals aiming to leverage technology for efficiency and compliance in decision-making.Jul 10, 2026LLM Agent Reasoning

6.8Scalable and Trustworthy Earth Observation Foundation ModelsUnderstanding how to adapt foundation models for Earth observation can enhance the reliability and effectiveness of remote sensing applications, which are crucial for environmental monitoring and decision-making.Jul 10, 2026Survey Multimodal Data

6.8Vision Foundation Models in Radiology: A Scoping Review of Data, Methodology, Evaluation and Clinical TranslationUnderstanding the current landscape of VFMs in radiology can guide future research and development towards more effective clinical applications.Jul 9, 2026Survey Data Evaluation

7.0A harmonised dataset for Earth system foundation modelsThis dataset enables the development of more comprehensive Earth system models by incorporating diverse data types, which can improve understanding and prediction of environmental changes and their socioeconomic impacts.Jul 7, 2026Data Multimodal Infra

6.8Translating Natural Language to Strategic Temporal Specifications via LLMsThis work is relevant for AI researchers and engineers interested in simplifying the specification process for multi-agent systems, potentially reducing the expertise barrier in formalizing system requirements.Jul 3, 2026LLM Agent Reasoning

6.8ALEE: Any-Language Evaluation of Embeddings via English-Centric Minimal PairsUnderstanding and improving cross-lingual semantic representation is crucial for developing more inclusive and effective language models, especially for low-resource languages.Jul 2, 2026Evaluation Benchmark Data

6.8VGGSounder: Audio-Visual Evaluations for Foundation ModelsImproving the evaluation of audio-visual models is crucial for developing more robust and reliable multi-modal AI systems.Jul 1, 2026Multimodal Evaluation Benchmark

7.2REMSA: Foundation Model Selection for Remote Sensing via a Constraint-Aware AgentThis work addresses the challenge of selecting appropriate foundation models for remote sensing tasks, potentially improving efficiency and accuracy in deploying these models for practical applications.Jul 1, 2026Agent Multimodal Evaluation

6.8Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training RegimesUnderstanding and modeling user intent can lead to more robust and reliable safety classifiers, which is crucial for deploying AI systems in sensitive or high-stakes environments.Jun 26, 2026LLM Safety Alignment

6.8Subjective-Graph LLM Agents for Simulating Uncertainty in Classroom Social PerceptionUnderstanding how subjective perceptions affect social dynamics in educational settings can inform interventions to improve academic and social outcomes.Jun 25, 2026LLM Agent Data

7.2Evaluating Japanese Dialect Robustness Across Speech and Text-based Large Language ModelsUnderstanding dialectal variations is crucial for developing effective dialogue systems, especially in linguistically diverse contexts like Japan.Jun 25, 2026LLM Evaluation Data

7.2LLM Performance on a Real, Double-Marked GCSE BenchmarkThis research demonstrates the potential for LLMs to automate the grading of exams, which could significantly reduce the workload of educators and standardize grading processes.Jun 25, 2026LLM Evaluation Benchmark

7.2Cosmos 3: Omnimodal World Models for Physical AIThis work could streamline the development of embodied AI systems by providing a versatile and unified model architecture that handles diverse data types, potentially accelerating advancements in robotics and multimodal AI applications.Jun 25, 2026Multimodal Vision Language Agent

7.2TerraMind: Large-Scale Generative Multimodality for Earth ObservationThis work could enhance Earth observation by providing a versatile model capable of handling multiple modalities and generating additional data, potentially improving analysis and decision-making in geospatial applications.Jun 20, 2026Multimodal Data Benchmark

7.2LegalWorld: A Life-Cycle Interactive Environment for Legal AgentsUnderstanding and evaluating legal agents in a life-cycle context can lead to more effective AI systems in legal domains, potentially improving legal processes and outcomes.Jun 18, 2026Agent Evaluation Benchmark

6.8Risk-Aware LLM Agents for Geospatial Data Retrieval: Design and Preliminary Adversarial EvaluationThis work is relevant for AI researchers and engineers working on integrating natural language processing with geospatial data systems, offering potential improvements in environmental monitoring and disaster response.Jun 16, 2026LLM Agent Data

6.8GlobeAudio: A Multilingual Multicultural Benchmark for Naturalistic Evaluation of Large Audio-Language ModelsUnderstanding the limitations of current LALMs in real-world, multilingual, and multicultural contexts is crucial for developing more effective and inclusive AI systems.Jun 9, 2026Multimodal Evaluation Benchmark

7.2A robust PPG foundation model using multimodal physiological supervisionThis approach could lead to more reliable PPG-based applications in consumer devices and clinical settings by improving model performance on noisy data.Jun 8, 2026Multimodal Data

7.2TRACE: A Temporal Conditional Estimation for Multimodal Time Series Foundation ModelsThis work is relevant for AI researchers and engineers dealing with real-world multimodal time series data, as it offers a method to improve model robustness and accuracy in the presence of missing or irregular data.Jun 6, 2026Multimodal Data

6.8CL-DMDF:Dynamic Multimodal Data Fusion Model Based on Contrastive LearningThe approach addresses the challenge of missing or uncertain modality inputs in real-world multimodal data fusion, potentially improving decision-making processes in complex environments.Jun 3, 2026Multimodal Data

7.5AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked ModelingThis work addresses the critical challenge of generating human motion across multiple modalities, which is essential for advancements in robotics and computer vision applications.May 29, 2026Multimodal Data Robotics

7.2FLORO: A Multimodal Geospatial Foundation Model for Ecological Remote Sensing Across Sensors and ScalesThis work is relevant for AI researchers and engineers working on remote sensing applications, as it demonstrates effective model performance with smaller datasets, which is crucial for ecological and environmental monitoring.May 28, 2026Multimodal Data Benchmark

7.5Towards Autonomous Mechanistic Reasoning in Virtual CellsThis research addresses the critical gap in factually grounded explanations in biology, which can enhance the reliability of scientific discovery using AI.May 22, 2026LLM Agent Reasoning

6.8Structure-BiEval: A Self-Supervised, Dual-Track Framework for Decoupling Structure and Content in LLM Evaluation for Web Information SystemsUnderstanding and improving the structural fidelity of LLMs is crucial for their effective deployment in web-based systems, where accurate data formatting is essential for API interactions and data exchange.May 18, 2026LLM Evaluation Data

7.2Do Chinese models speak Chinese languages?Understanding the language capabilities of AI models is crucial for addressing the needs of diverse populations and informing resource allocation in AI development.May 18, 2026LLM Evaluation Data

7.5Continual Learning with Multilingual Foundation ModelThis research is significant for improving the understanding of language dynamics in social media, particularly in the context of LGBTQ+ discourse, which can inform both academic research and practical applications in moderation tools.May 14, 2026LLM Evaluation Data

7.0LLMs as annotators of credibility assessment in Danish asylum decisions: evaluating classification performance and errors beyond aggregated metricsUnderstanding LLM performance in specialized legal domains can improve automated text annotation, potentially reducing costs and increasing efficiency in legal processes.May 14, 2026LLM Evaluation Benchmark

7.5LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due DiligenceThis research addresses a critical need in the biotech industry for efficient and accurate competitor analysis, potentially saving significant time and resources for investors.May 11, 2026LLM Agent Evaluation

7.2Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing RobustnessThis research addresses the challenge of missing data in multimodal medical imaging, which is crucial for developing more generalizable and robust AI models in healthcare.May 11, 2026Multimodal Data

7.5Data Language Models: A New Foundation Model Class for Tabular DataThis work addresses a significant gap in AI by providing a native understanding of tabular data, which is crucial for many real-world applications and decision-making processes.May 8, 2026Data

7.2Understanding Annotator Safety Policy with InterpretabilityUnderstanding the reasons behind annotation disagreements can lead to more effective and inclusive AI safety policies, which is crucial for developing reliable AI systems.May 8, 2026Safety Interpretability Data

7.2Mind the Gap? A Distributional Comparison of Real and Synthetic Priors for Tabular Foundation ModelsUnderstanding the differences in data distributions is crucial for improving the performance and generalization of AI models, especially in tabular data applications.May 8, 2026Data Evaluation