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Zhengyang Liu

Publications and source records attributed to Zhengyang Liu.

At least 19 recordsLinked to original sources

Tight Inapproximability of Pacing and Throttling Equilibria in Second-Price Auctions

Budget-constrained advertisers commonly rely on two control mechanisms: pacing scales bids, whereas throttling randomizes participation. We prove that, in second-price auctions, these two different mechanisms share the same sharp approximation-hardness threshold. For pacing, computing a $\gamma$-approximate equilibrium is $\mathsf{PPAD}$-hard for every constant $\gamma\in[0,1)$. For throttling, computing a $\delta$-approximate equilibrium is $\mathsf{PPAD}$-hard for every constant $\delta\in(0,1)$. At parameter $1$, the complementarity requirement becomes vacuous and the all-zero solution is feasible. That is, approximation does not eliminate the fixed-point barrier at any nontrivial parameter value.

cs.GT

Support Contraction for Well-Supported Nash Equilibria

We introduce the support contraction, a structural procedure for computing well-supported Nash equilibria (WSNE) in bimatrix games. On a common action rectangle, the procedure alternately retains the support of a row maximin strategy for the row-payoff matrix and the support of a column maximin strategy for the column-payoff matrix. Each restriction preserves the value of the matrix game that selected it and can only increase the other value. At a stable rectangle, full support of the two maximizing strategies and complementary slackness make every surviving action tight. Crossing the two minimax strategies then gives an exact Nash equilibrium of the retained subgame, while the two zero-sum values bound deviations to deleted actions. Support contraction gives a deterministic polynomial-time algorithm that computes a $1/2$-WSNE of every rational bimatrix game with payoffs in $[0,1]$, with no additive slack, and a deterministic $O(\epsilon^{-2}\log^2 n)$-bit two-party protocol for a $(1/2+\epsilon)$-WSNE. The same support-contraction certificate, preceded by randomized one-sided localization, gives an $O(\epsilon^{-2}n\log n)$ payoff-query algorithm for the same guarantee, improving the $\epsilon^{-4}$ dependence to $\epsilon^{-2}$.

cs.GT

Approximation and Irrationality in Hylland--Zeckhauser Equilibria

We study the computation of Hylland--Zeckhauser (HZ) equilibria beyond the bi-valued setting. First, we give a polynomial-time algorithm that, for general multi-valued utilities, computes an $1/e$-approximate HZ equilibrium. This yields, to our knowledge, the first polynomial-time constant-error approximation guarantee for this setting. The key technical ingredient is a utility-stratification construction that embeds a multi-valued market into a structured bi-valued instance, allowing us to apply the exact algorithm of Vazirani and Yannakakis. Second, we show that the rational structure of exact equilibria breaks down already for tri-valued utilities: there exists a $5\times5$ HZ instance with utilities in $\{0,\frac12,1\}$ such that all of whose equilibria are irrational. Taken together, these results show that while the bi-valued case can be used as a base for approximation algorithms, rational exact equilibria cannot be guaranteed even for tri-valued utilities.

cs.GT

Second-Best Bilateral Trade is $1/2$ Efficient

The landmark Myerson-Satterthwaite Theorem establishes a fundamental impossibility in bilateral trade: no Bayesian incentive-compatible mechanism can simultaneously achieve ex-post efficiency, individual rationality, and strong budget balance. We resolve a long-standing open question regarding the efficiency loss imposed by these constraints. Specifically, we prove that the Bayesian-optimal (second-best) mechanism always captures at least half of the first-best gains from trade ($\mathrm{SB}\ge\frac{1}{2}\mathrm{FB}$). This result is tight, definitively closing the gap between the previously best-known bounds of $0.317$ and $0.736$.

cs.GT

Pacing Equilibria in Second-Price Auctions with Few Goods

In this paper, we investigate the computation of second-price pacing equilibria (SPPEs), a foundational model in online advertising auctions. We present a polynomial-time algorithm for computing exact SPPEs in instances with a constant number of goods. Our core technique maps buyers' pacing multipliers to the highest bids on each good, effectively partitioning the parameter space into a set of distinct geometric cells. By enumerating these cells, we fix the relative ordering of the bids and reduce the problem of equilibrium computation to a linear feasibility program. Finally, we demonstrate that this tractability extends to large-scale markets with an arbitrary number of goods, provided the goods can be aggregated into a constant number of valuation types.

cs.GT

EpiBench: Benchmarking Multi-turn Research Workflows for Multimodal Agents

Scientific research follows multi-turn, multi-step workflows that require proactively searching the literature, consulting figures and tables, and integrating evidence across papers to align experimental settings and support reproducible conclusions. This joint capability is not systematically assessed in existing benchmarks, which largely under-evaluate proactive search, multi-evidence integration and sustained evidence use over time. In this work, we introduce EpiBench, an episodic multi-turn multimodal benchmark that instantiates short research workflows. Given a research task, agents must navigate across papers over multiple turns, align evidence from figures and tables, and use the accumulated evidence in the memory to answer objective questions that require cross paper comparisons and multi-figure integration. EpiBench introduces a process-level evaluation framework for fine-grained testing and diagnosis of research agents. Our experiments show that even the leading model achieves an accuracy of only 29.23% on the hard split, indicating substantial room for improvement in multi-turn, multi-evidence research workflows, providing an evaluation platform for verifiable and reproducible research agents.

cs.CL

LLMs Judge Themselves: A Game-Theoretic Framework for Human-Aligned Evaluation

Ideal or real - that is the question.In this work, we explore whether principles from game theory can be effectively applied to the evaluation of large language models (LLMs). This inquiry is motivated by the growing inadequacy of conventional evaluation practices, which often rely on fixed-format tasks with reference answers and struggle to capture the nuanced, subjective, and open-ended nature of modern LLM behavior. To address these challenges, we propose a novel alternative: automatic mutual evaluation, where LLMs assess each other's output through self-play and peer review. These peer assessments are then systematically compared with human voting behavior to evaluate their alignment with human judgment. Our framework incorporates game-theoretic voting algorithms to aggregate peer reviews, enabling a principled investigation into whether model-generated rankings reflect human preferences. Empirical results reveal both convergences and divergences between theoretical predictions and human evaluations, offering valuable insights into the promises and limitations of mutual evaluation. To the best of our knowledge, this is the first work to jointly integrate mutual evaluation, game-theoretic aggregation, and human-grounded validation for evaluating the capabilities of LLMs.

cs.CL

PRIM: Towards Practical In-Image Multilingual Machine Translation

In-Image Machine Translation (IIMT) aims to translate images containing texts from one language to another. Current research of end-to-end IIMT mainly conducts on synthetic data, with simple background, single font, fixed text position, and bilingual translation, which can not fully reflect real world, causing a significant gap between the research and practical conditions. To facilitate research of IIMT in real-world scenarios, we explore Practical In-Image Multilingual Machine Translation (IIMMT). In order to convince the lack of publicly available data, we annotate the PRIM dataset, which contains real-world captured one-line text images with complex background, various fonts, diverse text positions, and supports multilingual translation directions. We propose an end-to-end model VisTrans to handle the challenge of practical conditions in PRIM, which processes visual text and background information in the image separately, ensuring the capability of multilingual translation while improving the visual quality. Experimental results indicate the VisTrans achieves a better translation quality and visual effect compared to other models. The code and dataset are available at: https://github.com/BITHLP/PRIM.

cs.CL

A Performance Model for Warp Specialization Kernels

This paper presents a performance model tailored for warp specialization kernels, focusing on factors such as warp size, tilling size, input matrix size, memory bandwidth, and thread divergence. Our model offers accurate predictions of execution time by leveraging differential equations validated through simulations and experiments. The insights gained from this model not only enhance our understanding of warp specialization techniques but also have practical implications for optimizing GPU-accelerated applications through compiler optimizations, kernel parameter tuning, and algorithm design.

cs.PL

Acoustic-Driven Surface Cleaning with Millimeter-Sized Bubbles at Translational Resonance

Traditional surface cleaning methods often suffer from drawbacks such as chemical harshness, potential for surface damage, and high energy consumption. This study investigates an alternative approach: acoustic-driven surface cleaning using millimeter-sized bubbles excited at low, sub-cavitation frequencies. We identify and characterize a distinct translational resonance of these bubbles, occurring at significantly lower frequencies (e.g., 50 Hz for 1.3 mm diameter bubbles) than the Minnaert resonance for a bubble of the same size. Experiments reveal that at this translational resonance, stationary bubbles exhibit amplified lateral swaying, while bubbles sliding on an inclined surface display pronounced "stop-and-go" dynamics. The theoretical model treats the bubble as a forced, damped harmonic oscillator, where surface tension provides the restoring force and the inertia is dominated by the hydrodynamic added mass of the surrounding fluid. It accurately predicts the observed resonant frequency scaling with bubble size ($\propto R_0^{-3/2}$). Cleaning efficacy, assessed using protein-based artificial soil on glass slides, was improved by approximately 90\% when bubbles were driven at their translational resonant frequency compared to off-resonant frequencies or non-acoustic conditions. These findings demonstrate that leveraging translational resonance enhances bubble-induced shear and agitation, offering an effective and sustainable mechanism for surface cleaning.

cond-mat.soft

Exploring In-Image Machine Translation with Real-World Background

In-Image Machine Translation (IIMT) aims to translate texts within images from one language to another. Previous research on IIMT was primarily conducted on simplified scenarios such as images of one-line text with black font in white backgrounds, which is far from reality and impractical for applications in the real world. To make IIMT research practically valuable, it is essential to consider a complex scenario where the text backgrounds are derived from real-world images. To facilitate research of complex scenario IIMT, we design an IIMT dataset that includes subtitle text with real-world background. However previous IIMT models perform inadequately in complex scenarios. To address the issue, we propose the DebackX model, which separates the background and text-image from the source image, performs translation on text-image directly, and fuses the translated text-image with the background, to generate the target image. Experimental results show that our model achieves improvements in both translation quality and visual effect.

cs.CL

HandCept: A Visual-Inertial Fusion Framework for Accurate Proprioception in Dexterous Hands

As robotics progresses toward general manipulation, dexterous hands are becoming increasingly critical. However, proprioception in dexterous hands remains a bottleneck due to limitations in volume and generality. In this work, we present HandCept, the first visual-inertial proprioception framework designed to overcome the challenges of traditional joint angle estimation methods for dexterous hands. HandCept addresses the difficulty of achieving accurate and robust joint angle estimation in dynamic environments where both visual and inertial measurements are prone to noise and drift. It leverages a zero-shot learning approach using a wrist-mounted RGB-D camera and 9-axis IMUs, fused in real time via a latency-free Extended Kalman Filter (EKF). Our results show that HandCept achieves joint angle estimation errors generally between $2^{\circ}$ and $4^{\circ}$ without observable drift, outperforming visual-only and inertial-only methods. Furthermore, we validate the stability and uniformity of the IMU system, demonstrating that a common base frame across IMUs simplifies system calibration. To support sim-to-real transfer, we also open-source our high-fidelity rendering pipeline, which is essential for training without real-world ground truth. This work offers a robust, generalizable solution for proprioception in dexterous hands, with significant implications for robotic manipulation and human-robot interaction. https://github.com/huangjund/blenderYCB

cs.RO

On the Oscillations in Cournot Games with Best Response Strategies

In this paper, we consider the dynamic oscillation in the Cournot oligopoly model, which involves multiple firms producing homogeneous products. To explore the oscillation under the updates of best response strategies, we focus on the linear price functions. In this setting, we establish the existence of oscillations. In particular, we show that for the scenario of different costs among firms, the best response converges to either a unique equilibrium or a two-period oscillation. We further characterize the oscillations and propose linear-time algorithms for finding all types of two-period oscillations. To the best of our knowledge, our work is the first step toward fully analyzing the periodic oscillation in the Cournot oligopoly model.

econ.TH

Few-shot Sim2Real Based on High Fidelity Rendering with Force Feedback Teleoperation

Teleoperation offers a promising approach to robotic data collection and human-robot interaction. However, existing teleoperation methods for data collection are still limited by efficiency constraints in time and space, and the pipeline for simulation-based data collection remains unclear. The problem is how to enhance task performance while minimizing reliance on real-world data. To address this challenge, we propose a teleoperation pipeline for collecting robotic manipulation data in simulation and training a few-shot sim-to-real visual-motor policy. Force feedback devices are integrated into the teleoperation system to provide precise end-effector gripping force feedback. Experiments across various manipulation tasks demonstrate that force feedback significantly improves both success rates and execution efficiency, particularly in simulation. Furthermore, experiments with different levels of visual rendering quality reveal that enhanced visual realism in simulation substantially boosts task performance while reducing the need for real-world data.

cs.RO

Fringe around a Beet Slice: Wetting-induced Dimple in a Thin Liquid Film

When a slice of beet is placed on a plate with a thin layer of beet juice, one can observe a clear fringe around the beet, where the color is more translucent than the rest of the juice. The hypotheses in literature were inconsistent and limited, which motivated us to revisit this phenomenon. Using a motorized confocal displacement sensor, we measured the temporal evolution of the liquid surface profile across the fringe. Our findings suggest that a suction flow, induced by the capillary rise of the contact line, causes a dimple - a small concave depression - to form on the liquid surface. While surface tension and gravity tends to smooth out the dimple, viscous drag acts against them if the liquid film is sufficiently thin. Our scaling analysis correctly estimates the dependence of dimple lifetime on liquid properties and film thickness. We also capture the dimple formation dynamics by numerically solving the lubrication equation with the Young-Laplace equation. This work provides a new interpretation for a common phenomenon.

cond-mat.soft

Vortex transition and thermal mixing by pitching a perforated flexible panel

The effective transport of heat and mass is crucial to both industrial applications and physiological processes. Recent research has evaluated the benefit of using flexible reeds for triggering the vortex induced vibration to enhance mixing, as opposed to traditional techniques like rigid blender or static meshes. Inspired by the soft, porous, and moving fish gill lamellae, we proposed a new concept of thermal dispenser that prescribes active pitching motion to the leading edge of an otherwise passively flapping perforated panel. Experimental measurements revealed drastic differences between the steady leaky flow wake behind a statically deflected perforated panel and the periodic shedding wakes with complex vortex structure transitions behind an actuated perforated panel with or without chord-wise flexibility. A semi-empirical simulation of the thermal convection and diffusion takes the experimentally obtained velocity as input and yields the temperature results. Vortex dynamics, Lagrangian coherent structures, and thermal mixing behaviors were analyzed and compared to elucidate the effects of kinematics, perforation, and flexibility on the wake mode transitions, lateral entrainment mixing, and overall heating. Our work provides a foundational understanding of the fluid-structure interactions of perforated bendable panels under active control which has not been described before in the intermediate Reynolds number range. It provides insights for developing an innovative bio-inspired heat or mass dispenser potentially suitable for subtle and small scale applications.

physics.flu-dyn

Active bacterial baths in droplets

Suspensions of self-propelled objects represent a novel paradigm in colloidal science. In such active baths traditional concepts, such as Brownian motion, fluctuation-dissipation relations, and work extraction from heat reservoirs, must be extended beyond the conventional framework of thermal baths. Unlike thermal baths, which are characterized by a single parameter, the temperature, the fundamental descriptors of an active bath remain elusive, especially in confined environments. In this study, buoyant, passive tracers are employed as generalized probes to investigate an active bath comprising motile bacteria confined within a droplet. We demonstrate that momentum transfer from the bath to the tracer can be effectively described as colored noise, characterized by temporal memory and an enhanced effective diffusivity significantly larger compared to thermal Brownian motion values. Using a stochastic analytical framework, we extract the temporal memory and diffusivity parameters that define such an active bath. Notably, the diffusivity scales linearly with bacterial concentration, modulated by a factor representing the role of confinement, expressed as the ratio of the confining radius to the probe radius. This finding, while still awaiting a complete theoretical explanation, offers new insights into the transport properties of confined active baths and paves the way for a deeper understanding of active emulsions driven by confined active matter.

cond-mat.soft

Minotaur: A SIMD-Oriented Synthesizing Superoptimizer

A superoptimizing compiler--one that performs a meaningful search of the program space as part of the optimization process--can find optimization opportunities that are missed by even the best existing optimizing compilers. We created Minotaur: a superoptimizer for LLVM that uses program synthesis to improve its code generation, focusing on integer and floating-point SIMD code. On an Intel Cascade Lake processor, Minotaur achieves an average speedup of 7.3\% on the GNU Multiple Precision library (GMP)'s benchmark suite, with a maximum speedup of 13\%. On SPEC CPU 2017, our superoptimizer produces an average speedup of 1.5\%, with a maximum speedup of 4.5\% for 638.imagick. Every optimization produced by Minotaur has been formally verified, and several optimizations that it has discovered have been implemented in LLVM as a result of our work.

cs.PL