Optimal Auctions vs. Anonymous Pricing: Beyond Linear Utility

The revenue optimal mechanism for selling a single item to agents with independent but non-identically distributed values is complex for agents with linear utility (Myerson,1981) and has no closed-form characterization for agents with non-linear utility (cf. Alaei et al., 2012). Nonetheless, for linear utility agents satisfying a natural regularity property, Alaei et al. (2018) showed that simply posting an anonymous price is an e-approximation. We give a parameterization of the regularity property that extends to agents with non-linear utility and show that the approximation bound of anonymous pricing for regular agents approximately extends to agents that satisfy this approximate regularity property. We apply this approximation framework to prove that anonymous pricing is a constant approximation to the revenue optimal single-item auction for agents with public-budget utility, private-budget utility, and (a special case of) risk-averse utility.Comment: Appeared at EC 201

Simple Mechanisms for Non-linear Agents

We consider agents with non-linear preferences given by private values and private budgets. We quantify the extent to which posted pricing approximately optimizes welfare and revenue for a single agent. We give a reduction framework that extends the approximation of multi-agent pricing-based mechanisms from linear utility to nonlinear utility. This reduction framework is broadly applicable as Alaei et al. (2012) have shown that mechanisms for linear agents can generally be interpreted as pricing-based mechanisms. We give example applications of the framework to oblivious posted pricing (e.g., Chawla et al., 2010), sequential posted pricing (e.g., Yan, 2011), and virtual surplus maximization (Myerson, 1981)

Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response

Classic mechanism/information design imposes the assumption that agents are fully rational, meaning each of them always selects the action that maximizes her expected utility. Yet many empirical evidence suggests that human decisions may deviate from this full rationality assumption. In this work, we attempt to relax the full rationality assumption with bounded rationality. Specifically, we formulate the bounded rationality of an agent by adopting the quantal response model (McKelvey and Palfrey, 1995). We develop a theory of rationality-robust information design in the canonical setting of Bayesian persuasion (Kamenica and Gentzkow, 2011) with binary receiver action. We first identify conditions under which the optimal signaling scheme structure for a fully rational receiver remains optimal or approximately optimal for a boundedly rational receiver. In practice, it might be costly for the designer to estimate the degree of the receiver's bounded rationality level. Motivated by this practical consideration, we then study the existence and construction of robust signaling schemes when there is uncertainty about the receiver's bounded rationality level

Competitive Information Disclosure with Multiple Receivers

This paper analyzes a model of competition in Bayesian persuasion in which two symmetric senders vie for the patronage of multiple receivers by disclosing information about the qualities (i.e., binary state -- high or low) of their respective proposals. Each sender is allowed to commit to a signaling policy where he sends a private (possibly correlated) signal to every receiver. The sender's utility is a monotone set function of receivers who make a patron to this sender. We characterize the equilibrium structure and show that the equilibrium is not unique (even for simple utility functions). We then focus on the price of stability (PoS) in the game of two senders -- the ratio between the best of senders' welfare (i.e., the sum of two senders' utilities) in one of its equilibria and that of an optimal outcome. When senders' utility function is anonymous submodular or anonymous supermodular, we analyze the relation between PoS with the ex ante qualities $\lambda$ (i.e., the probability of high quality) and submodularity or supermodularity of utility functions. In particular, in both families of utility function, we show that $\text{PoS} = 1$ when the ex ante quality $\lambda$ is weakly smaller than $1/2$, that is, there exists equilibrium that can achieve welfare in the optimal outcome. On the other side, we also prove that $\text{PoS} > 1$ when the ex ante quality $\lambda$ is larger than $1/2$, that is, there exists no equilibrium that can achieve the welfare in the optimal outcome. We also derive the upper bound of $\text{PoS}$ as a function of $\lambda$ and the properties of the value function. Our analysis indicates that the upper bound becomes worse as the ex ante quality $\lambda$ increases or the utility function becomes more supermodular (resp.\ submodular)

Enhanced Crystallinity of Triple-Cation Perovskite Film via Doping NH\u3csub\u3e4\u3c/sub\u3eSCN

The trap-state density in perovskite films largely determines the photovoltaic performance of perovskite solar cells (PSCs). Increasing the crystal grain size in perovskite films is an effective method to reduce the trap-state density. Here, we have added NH4SCN into perovskite precursor solution to obtain perovskite films with an increased crystal grain size. The perovskite with increased crystal grain size shows a much lower trap-state density compared with reference perovskite films, resulting in an improved photovoltaic performance in PSCs. The champion photovoltaic device has achieved a power conversion efficiency of 19.36%. The proposed method may also impact other optoelectronic devices based on perovskite films

ZnCuInS/ZnSe/ZnS Quantum Dot-Based Downconversion Light-Emitting Diodes and Their Thermal Effect

The quantum dot-based light-emitting diodes (QD-LEDs) were fabricated using blue GaN chips and red-, yellow-, and green-emitting ZnCuInS/ZnSe/ZnS QDs. The power efficiencies were measured as 14.0 lm/W for red, 47.1 lm/W for yellow, and 62.4 lm/W for green LEDs at 2.6 V. The temperature effect of ZnCuInS/ZnSe/ZnS QDs on these LEDs was investigated using CIE chromaticity coordinates, spectral wavelength, full width at half maximum (FWHM), and power efficiency (PE). The thermal quenching induced by the increased surface temperature of the device was confirmed to be one of the important factors to decrease power efficiencies while the CIE chromaticity coordinates changed little due to the low emission temperature coefficients of 0.022, 0.050, and 0.068 nm/°C for red-, yellow-, and green-emitting ZnCuInS/ZnSe/ZnS QDs. These indicate that ZnCuInS/ZnSe/ZnS QDs are more suitable for downconversion LEDs compared to CdSe QDs

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan