Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing
Kavli Affiliate: Xiang Zhang | First 5 Authors: Zijie Qiu, Jiaqi Wei, Xiang Zhang, Sheng Xu, Kai Zou | Summary: De novo peptide sequencing is a critical task in proteomics. However, the performance of current deep learning-based methods is limited by the inherent complexity of mass spectrometry data and the heterogeneous distribution of noise signals, […]
Continue.. Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing
DECT-based Space-Squeeze Method for Multi-Class Classification of Metastatic Lymph Nodes in Breast Cancer
Kavli Affiliate: Xiang Zhang | First 5 Authors: Hai Jiang, Chushan Zheng, Jiawei Pan, Yuanpin Zhou, Qiongting Liu | Summary: Background: Accurate assessment of metastatic burden in axillary lymph nodes is crucial for guiding breast cancer treatment decisions, yet conventional imaging modalities struggle to differentiate metastatic burden levels and capture comprehensive lymph node characteristics. This […]
Continue.. DECT-based Space-Squeeze Method for Multi-Class Classification of Metastatic Lymph Nodes in Breast Cancer
Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Kai Zhang, Mengxian Lyu, Hongfang Liu, Lichao Sun | Summary: To advance biomedical vison-language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handling long text, explore strategies to efficiently adopt vision language models for diverse multi-modal biomedical […]
Continue.. Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
Kavli Affiliate: Cheng Peng | First 5 Authors: Cheng Peng, Kai Zhang, Mengxian Lyu, Hongfang Liu, Lichao Sun | Summary: To advance biomedical vison-language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handling long text, explore strategies to efficiently adopt vision language models for diverse multi-modal biomedical […]
Continue.. Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
LLM-based Generative Error Correction for Rare Words with Synthetic Data and Phonetic Context
Kavli Affiliate: Masaki Yamashita| First 5 Authors: Natsuo Yamashita, Natsuo Yamashita, , , | Summary:Generative error correction (GER) with large language models (LLMs) has emerged as an effective post-processing approach to improve automatic speech recognition (ASR) performance. However, it often struggles with rare or domain-specific words due to limited training data. Furthermore, existing LLM-based GER […]
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Resolving Intervalley Gaps and Many-Body Resonances in Moiré Superconductor
Kavli Affiliate: Stevan Nadj-Perge | Summary:Magic-angle twisted multilayer graphene stands out as a highly tunable class of moiré materials that exhibit strong electronic correlations and robust superconductivity. However, understanding the relations between the low-temperature superconducting phase and the preceding correlated phases established at higher temperatures remains a challenge. Here, we employ scanning tunneling microscopy and […]
Continue.. Resolving Intervalley Gaps and Many-Body Resonances in Moiré Superconductor
The Lyman-$α$ emitter bispectrum as a probe of reionization morphology
Kavli Affiliate: Martin Haehnelt | Summary:Ly$α$ emitters (LAEs) have now been discovered out to redshift $z=13$, and are valuable probes of the reionization history at redshifts beyond the reach of other currently available tracers. Most inferences of the neutral hydrogen fraction from LAE observations rely on one-point and two-point statistics like the luminosity function and […]
Continue.. The Lyman-$α$ emitter bispectrum as a probe of reionization morphology
The Double Tidal Disruption Event AT 2022dbl Implies That at Least Some “Standard” Optical TDEs are Partial Disruptions
Kavli Affiliate: Michael Fausnaugh | Summary:Flares produced following the tidal disruption of stars by supermassive black holes can reveal the properties of the otherwise dormant majority of black holes and the physics of accretion. In the past decade, a class of optical-ultraviolet tidal disruption flares has been discovered whose emission properties do not match theoretical […]
Continue.. The Double Tidal Disruption Event AT 2022dbl Implies That at Least Some “Standard” Optical TDEs are Partial Disruptions
Towards Realistic Detection Pipelines of Taiji: New Challenges in Data Analysis and High-Fidelity Simulations of Space-Based Gravitational Wave Antenna
Kavli Affiliate: Xian Chen| Summary: Taiji, a Chinese space-based gravitational wave (GW) detection project, aims to explore the millihertz GW universe with unprecedented sensitivity. By observing astrophysical and cosmological sources, including Galactic binaries, massive black hole binaries, extreme mass-ratio inspirals, and stochastic gravitational wave backgrounds, etc., Taiji is expected to deliver transformative insights into astrophysics, […]
Continue.. Towards Realistic Detection Pipelines of Taiji: New Challenges in Data Analysis and High-Fidelity Simulations of Space-Based Gravitational Wave Antenna