Ke Li
10 papers in the PaperMetrix corpus
Papers by this author
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Implicit Maximum Likelihood Estimation
2018 · arXiv (Cornell University)
Implicit probabilistic models are models defined naturally in terms of a sampling procedure and often induces a likelihood function that cannot be expressed explicitly. We develop a simple method for estimating parameters in implicit models …
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Bayesian Network Based Label Correlation Analysis For Multi-label Classifier Chain
2019 · arXiv (Cornell University)
Classifier chain (CC) is a multi-label learning approach that constructs a sequence of binary classifiers according to a label order. Each classifier in the sequence is responsible for predicting the relevance of one label. When …
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Strong Converse Exponent for Entanglement-Assisted Communication
2022 · arXiv (Cornell University)
We determine the exact strong converse exponent for entanglement-assisted classical communication of a quantum channel. Our main contribution is the derivation of an upper bound for the strong converse exponent which is characterized by the …
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A reconfigurable and compact subpipelined architecture for AES encryption and decryption
2023 · EURASIP Journal on Advances in Signal Processing
Abstract AES has been used in many applications to provide the data confidentiality. A new 32-bit reconfigurable and compact architecture for AES encryption and decryption is presented and implemented in non-BRAM FPG in this paper. …
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A novel prediction approach driven by graph representation learning for heavy metal concentrations
2024 · The Science of The Total Environment
The potential risk of heavy metals (HMs) to public health is an issue of great concern. Early prediction is an effective means to reduce the accumulation of HMs. The current prediction methods rarely take internal …
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Enhancing Electric Power Industry Image-Text Matching with Image Properties
2024
The electric power industry has many valuable images containing meaningful information, such as on-site physical and technical schematic images, which can guide employees in operation and learning. However, these images sleep in documents because they …
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Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
2025
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus remains on developing their capabilities in static image understanding. The …
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SCIM: Self-Correcting Iterative Mechanism for Retrieval-Augmented Generation
2026 · Electronics
Standard Retrieval-Augmented Generation (RAG) models are limited by their “one-shot” nature, failing to assess or improve answer quality dynamically. To address this, we introduce SCIM (Self-Correcting Iterative Mechanism), a framework featuring multi-dimensional evaluation and adaptive …
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A Pruned Rnnlm Lattice-Rescoring Algorithm for Automatic Speech Recognition
2018
Lattice-rescoring is a common approach to take advantage of recurrent neural language models in ASR, where a word-lattice is generated from 1st-pass decoding and the lattice is then rescored with a neural model, and ann-gram …
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A survey on multimodal large language models
2024 · National Science Review
Recently, the multimodal large language model (MLLM) represented by GPT-4V has been a new rising research hotspot, which uses powerful large language models (LLMs) as a brain to perform multimodal tasks. The surprising emergent capabilities …