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This paper addresses a significant gap in Conflict-free Replicated Data Types (CRDTs), which ensure strong eventual consistency but typically assume honest participants and do not handle Byzantine …
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This paper addresses the emerging challenge of detecting AI-generated text-rich images synthesized by state-of-the-art multimodal models, specifically OpenAI's GPT-Image-2
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This paper addresses the problem of automated classification of eclipsing binary (EB) star systems into three morphological classes — contact (CEB), detached (DEB), and semi-detached (SDEB) using ph…
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This paper addresses the challenge of adapting general-domain Vision-Language Models (VLMs) for Visual Question Answering (VQA) in the Remote Sensing (RS) domain, where high-resolution aerial image…
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This paper addresses a critical gap in human tutor training by developing an AI-driven assessment system that links tutor training performance to real-life tutor practice
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This article provides a comprehensive retrospective and prospective analysis of the intersection between artificial intelligence (AI) and systems engineering (SE), a field branded AI4SE/SE4AI
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This paper addresses the largely unexplored question of narrative content composition in large-scale web-based corpora used for training large language models (LLMs)
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This paper addresses a critical gap in governing autonomous agentic AI systems driven by large language models (LLMs) that invoke tools, manipulate data, and coordinate with peers across organizations
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The paper addresses the critical problem of reliably detecting when GPUs are executing ML training workloads versus inference or non-ML computations using only zero-overhead, privacy-preserving tel…
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Diffusion-Proof addresses inherent limitations of auto-regressive (AR) large language models (LLMs) in formal theorem proving, specifically their difficulty maintaining long-range coherence and ina…
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The paper addresses the longstanding analytic continuation (AC) problem encountered in quantum Monte Carlo (QMC) simulations, where one seeks to reconstruct dynamic frequency-dependent spectral fun…
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This paper addresses the limitations of existing large language model (LLM)-based multi-agent systems (MAS) in handling complex decision-making tasks characterized by stance entanglement—situations…
