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Indian court proceedings are held in English, so speakers of languages with limited translation technology have limited access to them. We present the first English Mizo parallel dataset of Indian court judgments. It con...
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Control structures and operability indices for plantwide processes are developed and compared on fixed simulated flowsheets, and the configuration of a study is rarely reported in a form that another group can reproduce....
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As LLMs expand their language coverage, evaluating how well they understand and represent diverse cultures becomes increasingly important. However, many benchmarks remain English-centric, with limited cultural coverage a...
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Natural-language software requirements often omit assumptions about performance, operating conditions, user behaviour, and domain constraints, affecting architecture, testing, and deployment. If undiscovered until implem...
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We consider the problem of binary sequence reconstruction where a sequence is transmitted multiple times over a channel, and each undergoes substitution errors by an arbitrary error vector of Hamming weight exactly $t$. ...
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Training generative models on synthetic data causes loss of diversity and a decrease in performance, a phenomenon known as model collapse. We study this degeneration spectrally in a controlled Markov setting. The eigenva...
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This study introduces GuideEvolve, a self-evolving agent framework incorporating expert guidance and three autonomous regulatory mechanisms, collectively termed the 3Ts: Think Fast and Slow, Throwback, and Termination by...
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Empirical exchange-correlation functionals are fitted on fixed orbitals but used self-consistently, so better energies often come with worse densities. We show that the Brillouin residual of a trained functional on the K...
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The Pandora spacecraft is a smallsat selected in NASA's inaugural class of Pioneers missions. The aim of the Pandora mission is to disentangle stellar activity signals from exoplanet atmospheric transmission spectroscopy...
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Increasing the attention context length significantly improves streaming video generation quality, while incurring prohibitive memory and computational costs as the context grows. Existing methods attempt to capture this...
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Vietnamese pre-trained encoders have improved rapidly, but the strongest ones are large, multilingual-vocabulary models or depend on external word segmentation, which makes them costly to deploy. We present GoiBERT, a fa...
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Recent Diffusion Language Models (DLMs) use Self-Conditioning (SC), or Loopholing, to improve their performance. While SC is traditionally seen as an auxiliary heuristic, its empirical success raises the question: can a ...
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Personalized federated learning must decide which clients should share representations. We introduce HDC-FL (Head-Derived Clustering for Personalized Federated Learning), which reads that decision off a signal shared-enc...
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Language models make it easy to build classifiers by simply prompting a model with the sample to classify. However, their predictions are neither deterministic nor uniformly reliable across samples. How can we combine pr...
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Evangelou, StankoviΔ, Kevrekidis and Transtrum compared analytic and data-driven assessments of parameter identifiability for the infinite-bus synchronous generator. Fisher information with the manifold boundary approxim...