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Found 9 papers, 1 papers with code
OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety
In addition to these benchmarks, we have implemented a phased public evaluation and benchmark update strategy to ensure that OpenEval is in line with the development of Chinese LLMs or even able to provide cutting-edge benchmark datasets to guide the development of Chinese LLMs.
Memory-Constrained Algorithms for Convex Optimization via Recursive Cutting-Planes
We propose a family of recursive cutting-plane algorithms to solve feasibility problems with constrained memory, which can also be used for first-order convex optimization.
Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal
For the feasibility problem, in which an algorithm only has access to a separation oracle, we show a stronger trade-off: for at most $d^{2-\delta}$ memory, the number of queries required is $\tilde\Omega(d^{1+\delta})$.
Direct Speech-to-speech Translation without Textual Annotation using Bottleneck Features
Speech-to-speech translation directly translates a speech utterance to another between different languages, and has great potential in tasks such as simultaneous interpretation.
Sparse and Safe Frequency Regulation for Inverter Intensive Microgrids
This paper developed a novel control approach for the sparse and safe frequency regulation for inverter intensive microgrids (MGs).
A Novel Chinese Dialect TTS Frontend with Non-Autoregressive Neural Machine Translation
In this paper, we propose a novel Chinese dialect TTS frontend with a translation module, which converts Mandarin text into dialectic expressions to improve the intelligibility and naturalness of synthesized speech.
Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech
In expressive speech synthesis, there are high requirements for emotion interpretation.
Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery
We show that a single, universal choice of the regularization parameter suffices to achieve reconstruction error proportional to the (a priori unknown) noise level.
A hybrid text normalization system using multi-head self-attention for mandarin
In this paper, we propose a hybrid text normalization system using multi-head self-attention.
