CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language Models

As an indispensable ingredient of intelligence, commonsense reasoning is crucial for large language models (LLMs) in real-world scenarios. In this paper, we propose CORECODE, a dataset that contains abundant commonsense knowledge manually annotated on dyadic dialogues, to evaluate the commonsense reasoning and commonsense conflict detection capabilities of Chinese LLMs. We categorize commonsense knowledge in everyday conversations into three dimensions: entity, event, and social interaction. For easy and consistent annotation, we standardize the form of commonsense knowledge annotation in open-domain dialogues as "domain: slot = value". A total of 9 domains and 37 slots are defined to capture diverse commonsense knowledge. With these pre-defined domains and slots, we collect 76,787 commonsense knowledge annotations from 19,700 dialogues through crowdsourcing. To evaluate and enhance the commonsense reasoning capability for LLMs on the curated dataset, we establish a series of dialogue-level reasoning and detection tasks, including commonsense knowledge filling, commonsense knowledge generation, commonsense conflict phrase detection, domain identification, slot identification, and event causal inference. A wide variety of existing open-source Chinese LLMs are evaluated with these tasks on our dataset. Experimental results demonstrate that these models are not competent to predict CORECODE's plentiful reasoning content, and even ChatGPT could only achieve 0.275 and 0.084 accuracy on the domain identification and slot identification tasks under the zero-shot setting. We release the data and codes of CORECODE at https://github.com/danshi777/CORECODE to promote commonsense reasoning evaluation and study of LLMs in the context of daily conversations.Comment: AAAI 202

CaHSL1 Acts as a Positive Regulator of Pepper Thermotolerance Under High Humidity and Is Transcriptionally Modulated by CaWRKY40

Pepper (Capsicum annuum) is an economically important vegetable and heat stress can severely impair pepper growth, development, and productivity. The molecular mechanisms underlying pepper thermotolerance are therefore important to understand but remain elusive. In the present study, we characterized the function of CaHSL1, encoding a HAESA-LIKE (HSL) receptor-like protein kinase (RLK), during the response of pepper to high temperature and high humidity (HTHH). CaHSL1 exhibits the typical structural features of an arginine-aspartate RLK. Transient overexpression of CaHSL1 in the mesophyll cells of Nicotiana benthamiana showed that CaHSL1 localizes throughout the cell, including the plasma membrane, cytoplasm, and the nucleus. CaHSL1 was significantly upregulated by HTHH or the exogenous application of abscisic acid but not by R. solanacearum inoculation. However, CaHSL1 was downregulated by exogenously applied salicylic acid, methyl jasmonate, or ethephon. Silencing of CaHSL1 by virus-induced gene silencing significantly was reduced tolerance to HTHH and downregulated transcript levels of an associated gene CaHSP24. In contrast, transient overexpression of CaHSL1 enhanced the transcript abundance of CaHSP24 and increased tolerance to HTHH, as manifested by enhanced optimal/maximal photochemical efficiency of photosystem II in the dark (Fv/Fm) and actual photochemical efficiency of photosystem II in the light. In addition, CaWRKY40 targeted the promoter of CaHSL1 and induced transcription during HTHH but not in response to R. solanacearum. All of these results suggest that CaHSL1 is directly modulated at the transcriptional level by CaWRKY40 and functions as a positive regulator in the response of pepper to HTHH

Evaluating Large Language Models: A Comprehensive Survey

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous downstream applications. Nevertheless, akin to a double-edged sword, LLMs also present potential risks. They could suffer from private data leaks or yield inappropriate, harmful, or misleading content. Additionally, the rapid progress of LLMs raises concerns about the potential emergence of superintelligent systems without adequate safeguards. To effectively capitalize on LLM capacities as well as ensure their safe and beneficial development, it is critical to conduct a rigorous and comprehensive evaluation of LLMs. This survey endeavors to offer a panoramic perspective on the evaluation of LLMs. We categorize the evaluation of LLMs into three major groups: knowledge and capability evaluation, alignment evaluation and safety evaluation. In addition to the comprehensive review on the evaluation methodologies and benchmarks on these three aspects, we collate a compendium of evaluations pertaining to LLMs' performance in specialized domains, and discuss the construction of comprehensive evaluation platforms that cover LLM evaluations on capabilities, alignment, safety, and applicability. We hope that this comprehensive overview will stimulate further research interests in the evaluation of LLMs, with the ultimate goal of making evaluation serve as a cornerstone in guiding the responsible development of LLMs. We envision that this will channel their evolution into a direction that maximizes societal benefit while minimizing potential risks. A curated list of related papers has been publicly available at https://github.com/tjunlp-lab/Awesome-LLMs-Evaluation-Papers.Comment: 111 page

Gate-dependent Pseudospin Mixing in Graphene/Boron Nitride Moire Superlattices

Electrons in graphene are described by relativistic Dirac-Weyl spinors with a two-component pseudospin1-12. The unique pseudospin structure of Dirac electrons leads to emerging phenomena such as the massless Dirac cone2, anomalous quantum Hall effect2, 3, and Klein tunneling4, 5 in graphene. The capability to manipulate electron pseudospin is highly desirable for novel graphene electronics, and it requires precise control to differentiate the two graphene sub-lattices at atomic level. Graphene/boron nitride (graphene/BN) Moire superlattice, where a fast sub-lattice oscillation due to B-N atoms is superimposed on the slow Moire period, provides an attractive approach to engineer the electron pseudospin in graphene13-18. This unusual Moire superlattice leads to a spinor potential with unusual hybridization of electron pseudospins, which can be probed directly through infrared spectroscopy because optical transitions are very sensitive to excited state wavefunctions. Here, we perform micro-infrared spectroscopy on graphene/BN heterostructure and demonstrate that the Moire superlattice potential is dominated by a pseudospin-mixing component analogous to a spatially varying pseudomagnetic field. In addition, we show that the spinor potential depends sensitively on the gate-induced carrier concentration in graphene, indicating a strong renormalization of the spinor potential from electron-electron interactions. Our study offers deeper understanding of graphene pseudospin structure under spinor Moire potential, as well as exciting opportunities to control pseudospin in two-dimensional heterostructures for novel electronic and photonic nanodevices

5-HTTLPR Polymorphism Impacts Task-Evoked and Resting-State Activities of the Amygdala in Han Chinese

Background: Prior research has shown that the amygdala of carriers of the short allele (s) of the serotonin transporter (5-HTT) gene (5-HTTLPR) have a larger response to negative emotional stimuli and higher spontaneous activity during the resting state than non-carriers. However, recent studies have suggested that the effects of 5-HTTLPR may be specific to different ethnic groups. Few studies have been conducted to address this issue. Methodology/Principal Findings: Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) was conducted on thirty-eight healthy Han Chinese subjects (l/l group, n = 19; s/s group, n = 19) during the resting state and during an emotional processing task. Compared with the s/s group, the l/l group showed significantly increased regional homogeneity or local synchronization in the right amygdala during the resting state (|t|.2.028, p,0.05, corrected), but no significant difference was found in the bilateral amygdala in response to negative stimuli in the emotional processing task. Conclusions/Significance: 5-HTTLPR can alter the spontaneous activity of the amygdala in Han Chinese. However, the effect of 5-HTTLPR on the amygdala both in task state and resting state in Asian population was no similar with Caucasians. The

VIRS based detection in combination with machine learning for mapping soil pollution

Widespread soil contamination threatens living standards and weakens global efforts towards the Sustainable Development Goals (SDGs). Detailed soil mapping is needed to guide effective countermeasures and sustainable remediation operations. Here, we review visible and infrared reflectance spectroscopy (VIRS) based detection methods in combination with machine learning. To date, proximal, airborne and spaceborne carrier devices have been employed for soil contamination detection, allowing large areas to be covered at low cost and with minimal secondary environmental impact. In this way, soil contaminants can be monitored remotely, either directly or through correlation with soil components (e.g. Fe oxides, soil organic matter, clay minerals). Observed vegetation reflectance spectra has also been proven an effective indicator for mapping soil pollution. Calibration models based on machine learning are used to interpret spectral data and predict soil contamination levels. The algorithms used for this include partial least squares regression, neural networks, and random forest. The processes underlying each of these approaches are outlined in this review. Finally, current challenges and future research directions are explored and discusse

Immobilization of Saccharomyces cerevisiae using polyethyleneimine grafted collagen fibre as support and investigations of its fermentation performance

In the present investigation, an collagen fibre (CF), abundant natural biomass, was successfully grafted by polyethyleneimine (PEI). The resultant PEI grafted collagen fibre (CF-PEI) was employed as biocompatible and high cell loading support matrix for the immobilization of Saccharomyces cerevisiae cells. The as-prepared CF-PEI immobilized cells (CF-PEI-cell) exhibited high activity and stability for both batch and continuous fermentation. In batch fermentation, CF-PEI-cells showed enhanced stability as compared with other matrices supported cells, and produced an average ethanol concentration of 45.04 g/L with ethanol yield (YP/S) of 0.46 g/g and glucose conversion efficiency (η) of 90.4%. Continuous fermentation was operated stably in a down-flow trickling bed reactor charged with CF-PEI-cell for a total of 2 months. When the dilution rate was 0.16 1/h, the average ethanol productivity reached 7.18 g/(L h) with η of 88.94%. Further scanning electron microscopy observations confirmed that yeast cells can proliferate on the surface of CF-PEI during ethanol fermentation, which demonstrates that CF-PEI is indeed an ideal matrix for the immobilization of yeast cells

Immobilization of Saccharomyces cerevisiae using polyethyleneimine grafted collagen fibre as support and investigations of its fermentation performance

In the present investigation, an collagen fibre (CF), abundant natural biomass, was successfully grafted by polyethyleneimine (PEI). The resultant PEI grafted collagen fibre (CF-PEI) was employed as biocompatible and high cell loading support matrix for the immobilization of Saccharomyces cerevisiae cells. The as-prepared CF-PEI immobilized cells (CF-PEI-cell) exhibited high activity and stability for both batch and continuous fermentation. In batch fermentation, CF-PEI-cells showed enhanced stability as compared with other matrices supported cells, and produced an average ethanol concentration of 45.04 g/L with ethanol yield (YP/S) of 0.46 g/g and glucose conversion efficiency (η) of 90.4%. Continuous fermentation was operated stably in a down-flow trickling bed reactor charged with CF-PEI-cell for a total of 2 months. When the dilution rate was 0.16 1/h, the average ethanol productivity reached 7.18 g/(L h) with η of 88.94%. Further scanning electron microscopy observations confirmed that yeast cells can proliferate on the surface of CF-PEI during ethanol fermentation, which demonstrates that CF-PEI is indeed an ideal matrix for the immobilization of yeast cells