arXiv subjects

Jinghua Liu

Publications and source records attributed to Jinghua Liu.

8 recordsLinked to original sources

arXiv2026

Giant Room-Temperature Third-Order Electrical Transport in a Thin-Film Altermagnet Candidate

Quantum geometry, a quantum mechanical quantity comprised of Berry curvature and quantum metric, describes the geometric structure of the electronic bands in solids. The correlation between nontrivial quantum geometry and quantum materials leads to new findings in condensed matter systems. Here we demonstrate that altermagnets, with spontaneously broken time-reversal (T)- half-lattice-translation and parity-time symmetry, host both T-odd and T-even quantum geometric quantities that simultaneously manifest themselves despite the vanishing net magnetization. Consequently, giant room-temperature third-order electrical transport responses with sizable quantum geometric contributions are observed in (101)-oriented RuO2 thin films, an altermagnetic candidate; in particular, the third-order Hall effect is intimately correlated with altermagnetic order and can serve as a promising tool for detecting the Neel vector. Our work not only supports the existence of altermagnetism in 8-nm-thick RuO2 thin films, but also shows altermagnets as a versatile platform for exploring quantum geometry and constructing quantum electronic and spintronic devices.

cond-mat.mes-hall↗

arXiv2025

Spin-Splitting Magnetoresistance in Altermagnetic RuO2 Thin Films

The recently discovered altermagnets, featured by the exotic correlation of magnetic exchange interaction and alternating crystal environments, have offered exciting cutting-edge opportunities for spintronics. Nevertheless, the altermagnetism of RuO2, one of the earliest-discovered altermagnets, is currently under intense debate. Here we try to resolve this controversy by demonstrating an altermagnetic spin-splitting magnetoresistance (SSMR) effect that is driven by a spin current associated with the giant nonrelativistic spin splitting of an altermagnet. Compared to the spin Hall magnetoresistance induced by a conventional relativistic spin current, the SSMR is characterized by unusual angular dependence with a phase-shift feature underpinned by the Neel-vector orientation and pronounced temperature dependence caused by its susceptibility to electron scattering. Through systematical investigations on the magnetoresistance of (101)-RuO2/Co bilayers, we disentangle a sizable SSMR and hence unveil a Neel vector along [001] direction. Our work not only demonstrates a simple electric avenue to probing the Neel vector of altermagnets, but also indicates long-range magnetic order in thin films of RuO2.

cond-mat.mes-hall↗

arXiv2024

Generating API Parameter Security Rules with LLM for API Misuse Detection

In this paper, we present a new framework, named GPTAid, for automatic APSRs generation by analyzing API source code with LLM and detecting API misuse caused by incorrect parameter use. To validate the correctness of the LLM-generated APSRs, we propose an execution feedback-checking approach based on the observation that security-critical API misuse is often caused by APSRs violations, and most of them result in runtime errors. Specifically, GPTAid first uses LLM to generate raw APSRs and the Right calling code, and then generates Violation code for each raw APSR by modifying the Right calling code using LLM. Subsequently, GPTAid performs dynamic execution on each piece of Violation code and further filters out the incorrect APSRs based on runtime errors. To further generate concrete APSRs, GPTAid employs a code differential analysis to refine the filtered ones. Particularly, as the programming language is more precise than natural language, GPTAid identifies the key operations within Violation code by differential analysis, and then generates the corresponding concrete APSR based on the aforementioned operations. These concrete APSRs could be precisely interpreted into applicable detection code, which proven to be effective in API misuse detection. Implementing on the dataset containing 200 randomly selected APIs from eight popular libraries, GPTAid achieves a precision of 92.3%. Moreover, it generates 6 times more APSRs than state-of-the-art detectors on a comparison dataset of previously reported bugs and APSRs. We further evaluated GPTAid on 47 applications, 210 unknown security bugs were found potentially resulting in severe security issues (e.g., system crashes), 150 of which have been confirmed by developers after our reports.

cs.CR↗

arXiv2024

The Midas Touch: Triggering the Capability of LLMs for RM-API Misuse Detection

In this paper, we propose an LLM-empowered RM-API misuse detection solution, ChatDetector, which fully automates LLMs for documentation understanding which helps RM-API constraints retrieval and RM-API misuse detection. To correctly retrieve the RM-API constraints, ChatDetector is inspired by the ReAct framework which is optimized based on Chain-of-Thought (CoT) to decompose the complex task into allocation APIs identification, RM-object (allocated/released by RM APIs) extraction and RM-APIs pairing (RM APIs usually exist in pairs). It first verifies the semantics of allocation APIs based on the retrieved RM sentences from API documentation through LLMs. Inspired by the LLMs' performance on various prompting methods,ChatDetector adopts a two-dimensional prompting approach for cross-validation. At the same time, an inconsistency-checking approach between the LLMs' output and the reasoning process is adopted for the allocation APIs confirmation with an off-the-shelf Natural Language Processing (NLP) tool. To accurately pair the RM-APIs, ChatDetector decomposes the task again and identifies the RM-object type first, with which it can then accurately pair the releasing APIs and further construct the RM-API constraints for misuse detection. With the diminished hallucinations, ChatDetector identifies 165 pairs of RM-APIs with a precision of 98.21% compared with the state-of-the-art API detectors. By employing a static detector CodeQL, we ethically report 115 security bugs on the applications integrating on six popular libraries to the developers, which may result in severe issues, such as Denial-of-Services (DoS) and memory corruption. Compared with the end-to-end benchmark method, the result shows that ChatDetector can retrieve at least 47% more RM sentences and 80.85% more RM-API constraints.

cs.CR↗

arXiv2023

Mpemba Effect in Crystallization of Polybutene-1

The Mpemba effect and its inverse can be understood as a result of nonequilibrium thermodynamics. In polymers, changes of state are generally non-equilibrium processes. However, the Mpemba effect has been rarely reported in the crystallization of polymers. In the melt, polybutene-1 (PB-1) has the lowest critical cooling rate in polyolefins and tends to maintain its original structure and properties with thermal history. A nascent PB-1 sample was prepared by using metallocene catalysis at low temperature, and the crystallization behavior and crystalline structure of the PB-1 were characterized by DSC and WAXS. Experimentally, a clear Mpemba effect is observed not only in the crystallization of the nascent PB-1 melt in form II but also in form I obtained from the nascent PB-1 at low melting temperature. It is proposed that this is due to the differences in the chain conformational entropy in the lattice which influence conformational relaxation times. The entropy and the relaxation time can be predicted using the Adam-Gibbs equations, whereas non-equilibrium thermodynamics is required to describe the crystallization with the Mpemba effect.

cond-mat.soft↗

arXiv2021

DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddings

Learning sentence embeddings from dialogues has drawn increasing attention due to its low annotation cost and high domain adaptability. Conventional approaches employ the siamese-network for this task, which obtains the sentence embeddings through modeling the context-response semantic relevance by applying a feed-forward network on top of the sentence encoders. However, as the semantic textual similarity is commonly measured through the element-wise distance metrics (e.g. cosine and L2 distance), such architecture yields a large gap between training and evaluating. In this paper, we propose DialogueCSE, a dialogue-based contrastive learning approach to tackle this issue. DialogueCSE first introduces a novel matching-guided embedding (MGE) mechanism, which generates a context-aware embedding for each candidate response embedding (i.e. the context-free embedding) according to the guidance of the multi-turn context-response matching matrices. Then it pairs each context-aware embedding with its corresponding context-free embedding and finally minimizes the contrastive loss across all pairs. We evaluate our model on three multi-turn dialogue datasets: the Microsoft Dialogue Corpus, the Jing Dong Dialogue Corpus, and the E-commerce Dialogue Corpus. Evaluation results show that our approach significantly outperforms the baselines across all three datasets in terms of MAP and Spearman's correlation measures, demonstrating its effectiveness. Further quantitative experiments show that our approach achieves better performance when leveraging more dialogue context and remains robust when less training data is provided.

cs.CL↗

arXiv2019

Conjugacy problem of strictly monotone maps with only one jump discontinuity

The conjugacy problem is one of the central questions in iteration theory. As far as we, for discontinuous strictly monotone maps there is no complete result. In this paper, we investigate the conjugacy problem of strictly monotone maps with only one jump discontinuity. We give some sufficient and necessary conditions for the conjugacy relationship. And we present some methods to construct all conjugacies. Furthermore, we present the conditions to guarantee $C^1$ smoothness of these conjugacies.

math.DS↗

arXiv2013

Giant magnetostriction in Tb-doped Fe83Ga17 melt-spun ribbons

Giant magnetostriction is achieved in the slightly Tb-doped Fe83Ga17 melt-spun ribbons. The tested average perpendicular magnetostriction is -886 ppm along the melt-spun ribbon direction in the Fe82.89Ga16.88Tb0.23 alloy. The calculated parallel magnetostriction is 1772 ppm, more than 4 times as large as that of binary Fe83Ga17 alloy. The enhanced magnetostriction should be attributed to a small amount of Tb solution into the A2 matrix phase during rapid solidification. The localized strong magnetocrystalline anisotropy of Tb element is suggested to cause the giant magnetostriction.

cond-mat.mtrl-sci↗