Are Large Language Models (LLMs) Good Social Predictors?

The prediction has served as a crucial scientific method in modern social studies. With the recent advancement of Large Language Models (LLMs), efforts have been made to leverage LLMs to predict the human features in social life, such as presidential voting. These works suggest that LLMs are capable of generating human-like responses. However, we find that the promising performance achieved by previous studies is because of the existence of input shortcut features to the response. In fact, by removing these shortcuts, the performance is reduced dramatically. To further revisit the ability of LLMs, we introduce a novel social prediction task, Soc-PRF Prediction, which utilizes general features as input and simulates real-world social study settings. With the comprehensive investigations on various LLMs, we reveal that LLMs cannot work as expected on social prediction when given general input features without shortcuts. We further investigate possible reasons for this phenomenon that suggest potential ways to enhance LLMs for social prediction

Electrical conductivity adjustment for interface capacitive-like storage in sodium-ion battery

Sodium-ion battery (SIB) is significant for grid-scale energy storage. However, a large radius of Na ions raises the difficulties of ion intercalation, hindering the electrochemical performance during fast charge/discharge. Conventional strategies to promote rate performance focus on the optimization of ion diffusion. Improving interface capacitive-like storage by tuning the electrical conductivity of electrodes is also expected to combine the features of the high energy density of batteries and the high power density of capacitors. Inspired by this concept, an oxide-metal sandwich 3D-ordered macroporous architecture (3DOM) stands out as a superior anode candidate for high-rate SIBs. Taking Ni-TiO2 sandwich 3DOM as a proof-of-concept, anatase TiO2 delivers a reversible capacity of 233.3 mAh g^-1 in half-cells and 210.1 mAh g^-1 in full-cells after 100 cycles at 50 mA g^-1. At the high charge/discharge rate of 5000 mA g^-1, 104.4 mAh g^-1 in half-cells and 68 mAh g^-1 in full-cells can also be obtained with satisfying stability. In-depth analysis of electrochemical kinetics evidence that the dominated interface capacitive-like storage enables ultrafast uptaking and releasing of Na-ions. This understanding between electrical conductivity and rate performance of SIBs is expected to guild future design to realize effective energy storage

Source attack of decoy-state quantum key distribution using phase information

Quantum key distribution (QKD) utilizes the laws of quantum mechanics to achieve information-theoretically secure key generation. This field is now approaching the stage of commercialization, but many practical QKD systems still suffer from security loopholes due to imperfect devices. In fact, practical attacks have successfully been demonstrated. Fortunately, most of them only exploit detection-side loopholes which are now closed by the recent idea of measurement-device-independent QKD. On the other hand, little attention is paid to the source which may still leave QKD systems insecure. In this work, we propose and demonstrate an attack that exploits a source-side loophole existing in qubit-based QKD systems using a weak coherent state source and decoy states. Specifically, by implementing a linear-optics unambiguous-state-discrimination measurement, we show that the security of a system without phase randomization --- which is a step assumed in conventional security analyses but sometimes neglected in practice --- can be compromised. We conclude that implementing phase randomization is essential to the security of decoy-state QKD systems under current security analyses.Comment: 12 pages, 5 figure