12 research outputs found
Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue
E-commerce pre-sales dialogue aims to understand and elicit user needs and
preferences for the items they are seeking so as to provide appropriate
recommendations. Conversational recommender systems (CRSs) learn user
representation and provide accurate recommendations based on dialogue context,
but rely on external knowledge. Large language models (LLMs) generate responses
that mimic pre-sales dialogues after fine-tuning, but lack domain-specific
knowledge for accurate recommendations. Intuitively, the strengths of LLM and
CRS in E-commerce pre-sales dialogues are complementary, yet no previous work
has explored this. This paper investigates the effectiveness of combining LLM
and CRS in E-commerce pre-sales dialogues, proposing two collaboration methods:
CRS assisting LLM and LLM assisting CRS. We conduct extensive experiments on a
real-world dataset of Ecommerce pre-sales dialogues. We analyze the impact of
two collaborative approaches with two CRSs and two LLMs on four tasks of
Ecommerce pre-sales dialogue. We find that collaborations between CRS and LLM
can be very effective in some cases.Comment: EMNLP 2023 Finding
T‑Gate Aligned Nanotube Radio Frequency Transistors and Circuits with Superior Performance
In this paper, we applied self-aligned T-gate design to aligned carbon nanotube array transistors and achieved an extrinsic current-gain cutoff frequency (<i>f</i><sub>t</sub>) of 25 GHz, which is the best on-chip performance for nanotube radio frequency (RF) transistors reported to date. Meanwhile, an intrinsic current-gain cutoff frequency up to 102 GHz is obtained, comparable to the best value reported for nanotube RF transistors. Armed with the excellent extrinsic RF performance, we performed both single-tone and two-tone measurements for aligned nanotube transistors at a frequency up to 8 GHz. Furthermore, we utilized T-gate aligned nanotube transistors to construct mixing and frequency doubling analog circuits operated in gigahertz frequency regime. Our results confirm the great potential of nanotube-based circuit applications and indicate that nanotube transistors are promising building blocks in high-frequency electronics
Self-Aligned T-Gate High-Purity Semiconducting Carbon Nanotube RF Transistors Operated in Quasi-Ballistic Transport and Quantum Capacitance Regime
Carbon nanotube RF transistors are predicted to offer good performance and high linearity when operated in the ballistic transport and quantum capacitance regime; however, realization of such transistors has been very challenging. In this paper, we introduce a self-aligned fabrication method for carbon nanotube RF transistors, which incorporate a T-shaped (mushroom-shaped) aluminum gate, with oxidized aluminum as the gate dielectric. In this way, the channel length can be scaled down to 140 nm, which enables quasi-ballistic transport, and the gate dielectric is reduced to 2–3 nm aluminum oxide, leading to quasi-quantum capacitance operation. A current-gain cutoff frequency (<i>f</i><sub>t</sub>) up to 23 GHz and a maximum oscillation frequency (<i>f</i><sub>max</sub>) of 10 GHz are demonstrated. Furthermore, the linearity properties of nanotube transistors are characterized by using the 1 dB compression point measurement with positive power gain for the first time, to our knowledge. Our work reveals the importance and potential of separated semiconducting nanotubes for various RF applications