P ers LEARN : Research Training through the Lens of Perspective Cultivation (2023)

Abstract: Scientific research is inherently shaped by its authors’ perspectives, influenced by various factorssuch as their personality, community, or society. Junior researchers often face challenges in identifying the perspectives reflected in the existing literature and struggle to develop their own viewpoints. In response to this issue, we introduce PersLEARN , a tool designed to facilitate the cultivation of scientific perspectives, starting from a basic seed idea and progressing to a well-articulated framework. By interacting with a prompt-based model, researchers can develop their perspectives explicitly. Our humanstudy reveals that scientific perspectives developed by students using PersLEARN exhibit a superior level of logical coherence and depth compared to those that did not. Furthermore, our pipeline outperforms baseline approaches across multiple domains of literature from various perspectives. These results suggest that PersLEARN could help foster a greater appreciation of diversity in scientific perspectives as an essential component of research training.

## introduction the pursuit of science is driven by a desire to gain a deeper understanding of the natural world, not only through the collection of objective facts but also through interpreting those facts @xcite . as a result, scientific knowledge is shaped by a complex interplay of various factors that extend beyond the objective world. these factors include the personal characteristics of individual scientists @xcite , shared mindsets within scientific communities @xcite , and broader societal contexts such as cultural and political influences @xcite @xcite . together, these factors contribute to forming perspectives regarding how best to interpret the natural world. perspectives are essential to effectively process and communicate scientific knowledge with limited cognitive resources @xcite @xcite . however, junior researchers often face difficulties in developing their own scientific perspectives. they may struggle to identify the perspectives reflected in the existing literature and consequently struggle to develop and articulate their own viewpoints. this presents a significant obstacle to the progress of research training and deprives junior researchers of the opportunity to embrace the broader range of diverse perspectives that could contribute to their understanding of a particular topic @xcite . the challenge of developing scientific perspectives is particularly evident in one of the most significant research training approaches-writing literature reviews. in our pilot study, we asked students studying at the intersection of artificial intelligence (ai) and cognitive reasoning (core) to write a review article from the perspective of "physics-based reasoning in computer vision (cv)" using a set of papers published on cv conferences. the assigned task aims to provide students with a multifaceted llms paper 3 paper 4 slice 3 slice 5 slice 4 slice 1 slice 2 llm prompt engineering ？ prompt evidence generator llm prompt engineering ？ prompt slice generator llm prompt engineering ？ prompt connection generator seed idea papers evidence proposals slice proposals connection proposals evidence slices interface long short-term memory sepp hochreiter et al,1997 evidence 1 evidence 2 slice 1 slice 2 evidence 1 evidence 2 a multiplicative input gate unit is introduced to protect the memory contents stored in j from perturbation by irrelevant inputs. likewise, a multiplicative output gate unit is introduced which protects other units from perturbation by currently irrelevant memory contents stored in j. the resulting, more complex unit is called a memory cell. as side benefit, self-attention could yield more interpretable models. we inspect attention distributions from our models and present and discuss examples in the appendix. not only do individual attention heads clearly learn to perform different tasks, many appear to exhibit behavior related to the syntactic and semantic structure of the sentences. an lstm unit uses a series of gates to control the flow of information through the unit, which makes its operations opaque. the transformer model can explicitly learn the attention distributions of the input sequence which is interpretable to some extent. or or or select evidence select evidence select evidence user seed idea model interpretability manually drag manually edit manually edit attention is all you need ashish vaswani et al,2017 31st conference on neural information processing systems (nips 2017), long beach, ca, usa long short-term memory sepp hochreiter et al,1997 neural computation 9(8):1735-1780 connection transformers generally offer a higher degree of interpretability than lstms due to their self-attention mechanism. seed idea interpreted seed idea interpreted attention is all you need ashish vaswani et al,2017 figure 2 : the interactive workflow of perslearn . this example showcases the scenario that a perslearn user intends to frame a rather novel perspective of "model interpretability" given the original papers on lstm and transformer. while the seed idea is not the major focus of both papers, evidence can be found to support that seed idea with the help of perslearn . the evidence includes the introduction of gates in lstm to protect memory contents and the self-attention mechanism in transformer, which can yield more interpretable models. then the user re-interprets the evidence that lstm operations are opaque due to the use of gates, while transformer models have some level of interpretability through their attention distributions. it concludes that transformers generally offer a higher degree of interpretability compared to lstms due to their self-attention mechanism. the process is assisted by prompt-engineered llms but is exactly determined by the user. perslearn is grounded in classical theories drawn from the fields of cognitive and social sciences, particularly in the domain of scientific knowledge representation (sec. 2.1). it provides an entire life-cycle of constructing a perspective frame that semi-automates researchers to start from a single seed idea and then iteratively interpret and structure relevant literature (sec. 2.2). this process is facilitated through an interactive system that employs a hierarchical prompt-based approach to propose potential interpretations and structures based on a seed idea (sec. 2.3). experiments on both hu-man evaluation (sec. 3) and automatic evaluation of each module (sec. 4) suggest that perslearn has the potential to enhance the quality of scientific research training significantly. ## design and implementation designing perslearn is required to answer two questions: (i) what is the appropriate representation of perspective frames that makes researchers comfortable? (ii) how to informationize such representation for both user input and automated generation? in response to the questions, we highlight how perslearn is implemented from a theoretical framework to an interactive system step by step. ## human evaluation to validate perslearn for research training, we conducted a human study following the standard protocols of digital device auxiliary scenarios in higher education @xcite . this study is approved by the institutional review board (irb) of peking university. ## automatic evaluation to automatically evaluate perslearn at scale, we introduce a perspective reconstruction task with three sub-tasks (slice generation, connection generation, and diversity evaluation), requiring the system to recover an established perspective frame given the same seed idea. ## discussion we present perslearn to facilitate scientific research training by explicitly cultivating perspectives. human study shows that perslearn significantly helps junior researchers set up the mindset for jumping out of perspective given by the literature and framing their own ones. extensive benchmarking shows that our system has the potential to mine perspectives out of diverse domains of literature without much human effort. these experiments suggest that perslearn has the potential to support scientific research training in generalfrom explicating one's own perspective to embracing the diverse perspectives of others. readers can refer to the "broader impact" and "limitation" sections (sec. 5) for further discussions. the human study presented in this work has been approved by the irb of peking university. we have been committed to upholding the highest ethical standards in conducting this study and ensuring the protection of the rights and welfare of all participants. considering that the workload of the procedure for participants is relatively high among all human studies, we paid the participants a wage of @xmath08.5/h). every expert was paid $240 for grading the 24 review paragraphs composed by the participants. we have obtained informed consent from all participants, including clear and comprehensive information about the purpose of the study, the procedures involved, the risks and benefits, and the right to withdraw at any time without penalty. participants were also assured of the confidentiality of their information. any personal data collected (including name, age, and gender) was handled in accordance with applicable laws and regulations.