Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?

Prompt tuning (PT) which only tunes the embeddings of an additional sequence of tokens per task, keeping the pre-trained language model (PLM) frozen, has shown remarkable performance in few-shot learning. Despite this, PT has been shown to rely heavily on good initialization of the prompt embeddings. In this work, we study meta prompt tuning (MPT) to systematically explore how meta-learning can help improve (if it can) cross-task generalization in PT through learning to initialize the prompt embeddings from other relevant tasks. We empirically analyze a representative set of meta learning algorithms in a wide range of adaptation settings with different source/target task configurations on a large set of few-shot tasks. With extensive experiments and analysis, we demonstrate the effectiveness of MPT. We find the improvement to be significant particularly on classification tasks. For other kinds of tasks such as question answering, we observe that while MPT can outperform PT in most cases, it does not always outperform multi-task learning. We further provide an in-depth analysis from the perspective of task similarity

Cylindrical roller bearing fault diagnosis based on VMD-SVD and Adaboost classifier method

Fault diagnosis for cylindrical roller bearing is of great significance for industry. In order to excavate the features of the vibration signal adequately, and to construct an effective classifier for complex vibration signals, this paper proposed a new fault diagnosis method based on Variational Mode Decomposition (VMD), Singular Value Decomposition (SVD) and Adaboost classifier. Firstly, the VMD was applied to decompose the sampled vibration signal in time-frequency domain. Subsequently, the features were extracted by using SVD. Finally, the constructed Adaboost classifier were employed to fault detection and diagnosis, which were trained by using the extracted features. Experimental data measured in a rotating machinery fault diagnosis experiment platform was used to verify the proposed method. The results demonstrate that the proposed method was effective to detect and diagnose the outer ring fault and rolling element fault in cylindrical roller bearing

ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning from human feedback, it showed that a model could answer human questions and follow instructions on a broad panel of tasks. Following this success, interests in LLMs have intensified, with new LLMs flourishing at frequent interval across academia and industry, including many start-ups focused on LLMs. While closed-source LLMs (e.g., OpenAI's GPT, Anthropic's Claude) generally outperform their open-source counterparts, the progress on the latter has been rapid with claims of achieving parity or even better on certain tasks. This has crucial implications not only on research but also on business. In this work, on the first anniversary of ChatGPT, we provide an exhaustive overview of this success, surveying all tasks where an open-source LLM has claimed to be on par or better than ChatGPT.Comment: version v4, included latest top-performing open-sourced LLM

Retrieving Multimodal Information for Augmented Generation: A Survey

As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world. However, there lacks a unified perception of at which stage and how to incorporate different modalities. In this survey, we review methods that assist and augment generative models by retrieving multimodal knowledge, whose formats range from images, codes, tables, graphs, to audio. Such methods offer a promising solution to important concerns such as factuality, reasoning, interpretability, and robustness. By providing an in-depth review, this survey is expected to provide scholars with a deeper understanding of the methods' applications and encourage them to adapt existing techniques to the fast-growing field of LLMs

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A Practice-Distributed Thunder-Localization System with Crowd-Sourced Smart IoT Devices

Lightning localization is of great significance to weather forecasting, forest fire prevention, aviation, military, and other aspects. Traditional lightning localization requires the deployment of base stations and expensive measurement equipment. With the development of IoT technology and the continuous expansion of application scenarios, IoT devices can be interconnected through sensors and other technical means to ultimately achieve the goal of automatic intelligent computing. Therefore, this paper proposes a low-cost distributed thunder-localization system based on IoT smart devices, namely ThunderLoc. The main idea of ThunderLoc is to collect dual-microphone data from IoT smart devices, such as smartphones or smart speakers, through crowdsourcing, turning the localization problem into a search problem in Hamming space. We studied the dual microphones integrated with smartphones and used the sign of Time Difference Of Arrival (TDOA) as measurement information. Through a simple generalized cross-correlation method, the TDOA of thunderclaps on the same smartphone can be estimated. After quantifying the TDOA measurement from the smartphone node, thunder localization was performed by minimizing the Hamming distance between the binary sequence and the binary vector measured in a database. The ThunderLoc system was evaluated through extensive simulations and experiments (a testbed with 30 smartphone nodes). The extensive experimental results demonstrate that ThunderLoc outperforms the main existing schemes in terms of effectively locating position and good robustness

Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework

As large language models (LLMs) have become the norm in NLP, demonstrating good performance in generation and reasoning tasks, one of its most fatal disadvantages is the lack of factual correctness. Generating unfactual texts not only leads to lower performances but also degrades the trust and validity of their applications. Chain-of-Thought (CoT) prompting improves trust and model performance on complex reasoning tasks by generating interpretable reasoning chains, but still suffers from factuality concerns in knowledge-intensive tasks. In this paper, we propose the Verify-and-Edit framework for CoT prompting, which seeks to increase prediction factuality by post-editing reasoning chains according to external knowledge. Building on top of GPT-3, our framework lead to accuracy improvements in multiple open-domain question-answering tasks

A 100 bp GAGA motif-containing sequence in AGAMOUS second intron is able to suppress the activity of CaMV35S enhancer in vegetative tissues.

Flower-specific promoters enable genetic manipulation of floral organs to improve crop yield and quality without affecting vegetative growth. However, the identification of strong tissue-specific promoters is a challenge. In addition, information on cis elements that is able to repress gene expression in vegetative tissues remains limited. Here, we report that fusing a 35S enhancer to the stamen- and carpel-specific NtAGIP1 promoter derived from the tobacco AGAMOUS second intron (AGI) can significantly increase the promoter activity. Interestingly, although the activity of the new promoter extends to sepals and pedicles, it does not cross the boundary of the reproductive organs. Serial deletion of the AGI and chromatin immunoprecipitation (ChIP) assay reveal a 100-bp fragment that contains a conserved GAGA factor binding motif contributes to the flower specificity by mediating histone H3 lysine 27 trimethylation (H3K27me3) modification of the promoter. Furthermore, this fragment shows significant suppressive effect on the activity of the 35S enhancer in vegetative tissues, consequently, resulting in a significant increase of the activity of 35S enhancer:AGI chimeric promoter without sacrifice of its specificity in inflorescence

Advancing Food Sovereignty and Justice through a UBC-Vancouver Climate-Friendly Food System (CFFS) Procurement Strategy

Globally, it is recognized that we are currently in the midst of a climate emergency. The phrase “climate emergency” acknowledges that human activity is responsible for increasing the earth’s global average temperature through the release of greenhouse gasses (GHGs) (UNEP, 2021). This declaration stresses the need for global leaders to take action and prioritize climate change mitigation in their policies (UNEP, 2021). UBC has created the Climate Action Plan (CAP 2030) to provide a trajectory towards net zero emissions (UBC Campus + Community Planning, 2021) to abide by the Paris Agreement, which stipulates that global warming must be limited to 1.5 degrees Celsius. Moreover, food was recognized as the second highest contributor to UBC’s GHG emissions (UBC, 2021). Food has also been identified as a significant area of focus for social advocacy and action (Block et al., 2011). Therefore, it is crucial to address the importance of climate-friendly food systems that foster food sovereignty and justice. To understand how climate change, food sovereignty and food justice intersect, it is pertinent to be conscious of what these terms entail in a university context. Within this report, food sovereignty is defined as “the right of peoples to healthy and culturally appropriate food produced through ecologically sound and sustainable methods” (Food Secure Canada, 2018, pp. 9). Food justice is referred to as a social value and action that acknowledges how factors such as settler-colonialism, workers’ rights, historical injustices and other social issues are embedded within the food system (Clendenning et al., 2015). In addition, both of these terms relate to recognizing power dynamics such as socioeconomic inequalities and minority groups (Clendenning et al., 2015; McMichael, 2014). A campus that exemplifies food sovereignty and justice must prioritize having sustainable, affordable food options, provide opportunities for consumers to practice ethical self-determination, and have programs that focus on advocating for the right to culturally diverse food (Laforge et al., 2021; McMichael, 2014). The purpose of this project was to foster a climate and socially-just food system within the UBC Vancouver campus in alignment with CAP 2030 goals. Furthermore, this project aimed to evaluate how campus stakeholders (e.g., students, faculty, administrators and food directors) understand and perceive current policies and procurement practices regarding food justice and food sovereignty and whether these values were being embodied within a campus context. We then used our research findings to develop a Climate-Friendly Food System (CFFS) Procurement Strategy that encapsulated the needs and interests of UBC stakeholders. This project was executed through a Community-Based Action Research (CBAR) approach. Our research was conducted through guidance of SEEDS, UBC Wellbeing, and UBC Campus & Community Planning. Our research identified key opportunities for fostering food justice and sovereignty within UBC Vancouver’s food procurement practices. Specifically, key stakeholders in food procurement, climate action, and policy planning (e.g., food directors, researchers, administrative staff) were identified and interviewed. Focus groups were used to assess how these stakeholders currently view institutional food system issues and whether they believe there are practices, policies or future opportunities on campus to further these values. Questions that were used in interviews and focus groups included topics on accessibility, availability and awareness of food justice and sovereignty in the food system. This project is significant as it holds UBC Vancouver’s food purchasing powers and policymakers accountable for cultivating food sovereignty and food justice to prioritizing the wellbeing of UBC community members. The project supports the UBC Vancouver community by suggesting a strategy that furthers UBC’s social and climate justice goals. This CFFS Food Procurement Strategy recommends targets, indicators, and actions that are intended to advance and operationalize food sovereignty and justice, as well as reduce food system-related GHG emissions as part of a more extensive CFFS Procurement Strategy. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”Land and Food Systems, Faculty ofUnreviewedUndergraduat