Leveraging Large Language Models in Conversational Recommender Systems

A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue. Recently, Large Language Models (LLMs) have exhibited an unprecedented ability to converse naturally and incorporate world knowledge and common-sense reasoning into language understanding, unlocking the potential of this paradigm. However, effectively leveraging LLMs within a CRS introduces new technical challenges, including properly understanding and controlling a complex conversation and retrieving from external sources of information. These issues are exacerbated by a large, evolving item corpus and a lack of conversational data for training. In this paper, we provide a roadmap for building an end-to-end large-scale CRS using LLMs. In particular, we propose new implementations for user preference understanding, flexible dialogue management and explainable recommendations as part of an integrated architecture powered by LLMs. For improved personalization, we describe how an LLM can consume interpretable natural language user profiles and use them to modulate session-level context. To overcome conversational data limitations in the absence of an existing production CRS, we propose techniques for building a controllable LLM-based user simulator to generate synthetic conversations. As a proof of concept we introduce RecLLM, a large-scale CRS for YouTube videos built on LaMDA, and demonstrate its fluency and diverse functionality through some illustrative example conversations

Can Arable Land Alone Ensure Food Security? The Concept of Arable Land Equivalent Unit and Its Implications in Zhoushan City, China

The requisition–compensation balance of farmlands (RCBF) is a strict Chinese policy that aims to ensure food security. However, the process of supplementing arable land has substantially damaged the ecological environment through the blind development of grasslands, woodlands, and wetlands to supplement arable land. Can arable land alone ensure food security? To answer this question, this study introduced the concepts of arable land equivalent unit (ALEU) and food equivalent unit (FEU) based on the idea of food security. Zhoushan City in Zhejiang Province, China was selected as the research area. This study analyzed the ALEU supply and demand capabilities in the study area and presented the corresponding policy implications for the RCBF improvement. The results showed that the proportion of ALEU from arable land and waters for aquaculture is from 46:54 in 2009 to 31:69 in 2015, thereby suggesting that aquaculture waters can also be important in food security. Under three different living standards (i.e., adequate food and clothing, well-off, and affluence), ALEU from arable land can barely meet the needs of the permanent resident population in the study area. However, ALEU from aquaculture waters can provide important supplementation. Therefore, we suggest that food supply capability from land types other than the arable land be taken seriously. Furthermore, RCBF can be improved with ALEU as core of the balance

Symmetric and antisymmetric surface plasmon polariton solitons in a metal-dielectric-metal waveguide with incoherent pumping

We propose a scheme to realize stable linear and nonlinear propagation of symmetric and antisymmetric surface plasmon polaritons (SPPs) solitons by doping ladder-type three-level quantum emitters into the middle layer of a metal-dielectric-metal (MDM) waveguide. In linear propagation regime, we show that both symmetric and antisymmetric SPPs can acquire a gain from electromagnetically induced transparency (EIT) effect with an incoherent pumping. The EIT can be used not only to completely compensate the Ohmic loss in the metal but also to acquire a subluminal group velocity for the SPPs. We also show that in nonlinear propagation regime a huge enhancement of Kerr nonlinearity of the symmetric and antisymmetric SPPs can be obtained but with different incoherent pumping intensities. As a result, gain-assisted (1+1)-dimensional symmetric and antisymmetric subluminal surface polaritonic solitons may be produced based on the strong confinement of electric field in the MDM waveguide. Our study may have promising applications in light information processing and transmission at nanoscale level based on MDM waveguides

What Drives Farmers to Participate in Rural Environmental Governance? Evidence from Villages in Sandu Town, Eastern China

Understanding farmers’ participation is crucial for achieving an effective impact on rural living environmental governance and promoting sustainable development. Taking Sandu Town in eastern China as a case study, in-depth semi-structured interviews with farmers, village cadres, and town managers were conducted in this study. Then, a conceptual framework incorporating comprehensive factors is presented to analyze the driving factors and mechanisms of farmer participation in rural domestic waste management. The results show that farmers’ participation in pro-environmental actions is a response to an integrated network of both internal and external factors. Life inertia, loss of personal interests, and objective conditions are the barriers to farmers deciding to participate. Meanwhile, environmental awareness can increase farmers’ internal motivations, and factors such as household benefits, social-cultural influences, and appraisal systems, including household possession protection, very low economic costs, better life experiences, demonstrations from society, “following the crowd”, peer pressure, and reward and criticism measures, are the external forces that mobilize farmers to participate in rural environmental governance. Policy recommendations are proposed based on the findings

What Drives Farmers to Participate in Rural Environmental Governance? Evidence from Villages in Sandu Town, Eastern China

Understanding farmers’ participation is crucial for achieving an effective impact on rural living environmental governance and promoting sustainable development. Taking Sandu Town in eastern China as a case study, in-depth semi-structured interviews with farmers, village cadres, and town managers were conducted in this study. Then, a conceptual framework incorporating comprehensive factors is presented to analyze the driving factors and mechanisms of farmer participation in rural domestic waste management. The results show that farmers’ participation in pro-environmental actions is a response to an integrated network of both internal and external factors. Life inertia, loss of personal interests, and objective conditions are the barriers to farmers deciding to participate. Meanwhile, environmental awareness can increase farmers’ internal motivations, and factors such as household benefits, social-cultural influences, and appraisal systems, including household possession protection, very low economic costs, better life experiences, demonstrations from society, “following the crowd”, peer pressure, and reward and criticism measures, are the external forces that mobilize farmers to participate in rural environmental governance. Policy recommendations are proposed based on the findings

openFEAT: Improving Speaker Identification by Open-set Few-shot Embedding Adaptation with Transformer

Household speaker identification with few enrollment utterances is an important yet challenging problem, especially when household members share similar voice characteristics and room acoustics. A common embedding space learned from a large number of speakers is not universally applicable for the optimal identification of every speaker in a household. In this work, we first formulate household speaker identification as a few-shot open-set recognition task and then propose a novel embedding adaptation framework to adapt speaker representations from the given universal embedding space to a household-specific embedding space using a set-to-set function, yielding better household speaker identification performance. With our algorithm, Open-set Few-shot Embedding Adaptation with Transformer (openFEAT), we observe that the speaker identification equal error rate (IEER) on simulated households with 2 to 7 hard-to-discriminate speakers is reduced by 23% to 31% relative.Comment: To appear in Proc. IEEE ICASSP 202