InAs/GaSb superlattice SESAM mode-locked fluoride fiber laser at 2.8 µm.

We demonstrate a mode-locked fluoride fiber laser operating at 2.8 µm using an InAs/GaSb superlattice (SL) semiconductor saturable absorber mirror (SESAM). Z-scan measurements show that the SL saturable absorber layer possesses off-bandgap nonlinearity near 2.

Nearly diffraction-limited picosecond pulse amplification from LMA fluoride fiber at 2.8 µm.

We demonstrated the generation of a nearly diffraction-limited picosecond pulse from a large-mode-area (LMA) fluoride fiber amplifier. Seeded with a mode-locked fiber oscillator at 2.8 µm, the LMA Er:ZBLAN fiber amplifier delivered the pulse of 16 µJ with a duration of 70 ps at 5 kHz.

LPN: Label-Enhanced Prototypical Network for Legal Judgment Prediction.

As one of the most critical tasks in legal artificial intelligence, legal judgment prediction (LJP) has garnered growing attention, especially in the civil law system. However, current methods often overlook the challenge of imbalanced label distributions, treating each label with equal importance, which can lead the model to be biased toward labels with high frequency. In this paper, we propose a label-enhanced prototypical network (LPN) suitable for LJP, that adopts a strategy of uniform encoding and separate decoding.

A Depth Evidence Score Fusion Algorithm for Chinese Medical Intelligence Question Answering System.

Question answering (QA) system is becoming the focus of the research in medical health in terms of providing fleetly accurate answers to users. Numerous traditional QA systems are faced to simple factual questions and do not obtain accurate answers for complex questions. In order to realize the intelligent QA system for disease diagnosis and treatment in medical informationization, in this paper, we propose a depth evidence score fusion algorithm for Chinese Medical Intelligent Question Answering System, which can measure the text information in many algorithmic ways and ensure that the QA system outputs accurately the optimal candidate answer.