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Runhua Zhang

Publications and source records attributed to Runhua Zhang.

11 recordsLinked to original sources

EGG: An Expert-Guided Agent Framework for Kernel Generation

High-performance GPU kernels are critical for reducing the exponentially growing computational costs of large language models (LLMs), but their development heavily relies on manual tuning by domain experts. While recent advances in LLM-based approaches show promise for automating kernel generation, they still struggle to achieve both correctness and high performance. This limitation primarily arises from the lack of domain-specific optimization guidance, hindering effective exploration of the optimization space. We propose EGG, an Expert-Guided Agent Framework for Kernel Generation, which incorporates expert optimization principles to guide LLMs' decisions. Inspired by expert workflows, we decompose kernel generation into two hierarchical stages: 1) algorithmic structure design, which establishes a high-quality computational structure foundation; 2) hardware-specific tuning, which performs targeted adjustments through parallel mapping, tensor tiling, and memory optimization. This staged decomposition defines explicit optimization objectives, structuring the design space to achieve progressive refinement. To this end, a stage-aware multi-agent collaboration mechanism is designed for inter and intra-stage context management, ensuring stable optimization trajectories. Experiments on KernelBench and real-world workloads show that EGG achieves a 2.13x average speedup over PyTorch, outperforming existing agent-based and RL-based approaches.

cs.AI

Unveiling Orbital-mediated Ultrafast Demagnetization in Rare Earth-Transition-Metal Ferrimagnets

The ultimate speed limit of magnetic recording and spintronic devices is set by the efficiency of angular-momentum transfer during ultrafast demagnetization, yet its microscopic pathway in Rare-Earth-Transition-Metal (RE-TM) ferrimagnets remains debated. Here, we establish an orbital-mediated framework in which 3d spin-orbit coupling (SOC) governs angular momentum (AM) dissipation. Strong 3d-SOC in RE-Co enables sub-picosecond, single-step demagnetization via direct orbital-to-lattice transfer, whereas weak 3d-SOC in RE-Fe redirects AM into 4f orbitals, producing slower two-step dynamics. The second-stage rate scales with 4f-SOC strength, revealing a distinct orbital-mediated dissipation channel. Using time-resolved magneto-optical Kerr measurements, supported by an extended four-temperature model, corroborate this picture across diverse RE-TM systems (RE = Sm, Gd, Tb, Dy, Ho and TM = Fe, Co, CoNi). Our results identify the SOC-driven competition between 3d and 4f orbital channels as the universal mechanism governing ultrafast demagnetization in RE-TM ferrimagnets, enabling rational design of the switching speed for next-generation spintronic devices.

cond-mat.mtrl-sci

"Without AI, I Would Never Share This Online": Unpacking How LLMs Catalyze Women's Sharing of Gendered Experiences on Social Media

Sharing gendered experiences on social media has been widely recognized as supporting women's personal sense-making and contributing to digital feminism. However, there are known concerns, such as fear of judgment and backlash, that may discourage women from posting online. In this study, we examine a recurring practice on Xiaohongshu, a popular Chinese social media platform, in which women share their gendered experiences alongside screenshots of conversations with LLMs. We conducted semi-structured interviews with 20 women to investigate whether and how interactions with LLMs might support women in articulating and sharing gendered experiences. Our findings reveal that, beyond those external concerns, women also hold self-imposed standards regarding what feels appropriate and worthwhile to share publicly. We further show how interactions with LLMs help women meet these standards and navigate such concerns. We conclude by discussing how LLMs might be carefully and critically leveraged to support women's everyday expression online.

cs.HC

When LLMs Enter Everyday Feminism on Chinese Social Media: Opportunities and Risks for Women's Empowerment

Everyday digital feminism refers to the ordinary, often pragmatic ways women articulate lived experiences and cultivate solidarity in online spaces. In China, such practices flourish on RedNote through discussions under hashtags like ''women's growth''. Recently, DeepSeek-generated content has been taken up as a new voice in these conversations. Given widely recognized gender biases in LLMs, this raises critical concerns about how LLMs interact with everyday feminist practices. Through an analysis of 430 RedNote posts, 139 shared DeepSeek responses, and 3211 comments, we found that users predominantly welcomed DeepSeek's advice. Yet feminist critical discourse analysis revealed that these responses primarily encouraged women to self-optimize and pursue achievements within prevailing norms rather than challenge them. By interpreting this case, we discuss the opportunities and risks that LLMs introduce for everyday feminism as a pathway toward women's empowerment, and offer design implications for leveraging LLMs to better support such practices.

cs.HC

Self-Imitated Diffusion Policy for Efficient and Robust Visual Navigation

Diffusion policies (DP) have demonstrated significant potential in visual navigation by capturing diverse multi-modal trajectory distributions. However, standard imitation learning (IL), which most DP methods rely on for training, often inherits sub-optimality and redundancy from expert demonstrations, thereby necessitating a computationally intensive "generate-then-filter" pipeline that relies on auxiliary selectors during inference. To address these challenges, we propose Self-Imitated Diffusion Policy (SIDP), a novel framework that learns improved planning by selectively imitating a set of trajectories sampled from itself. Specifically, SIDP introduces a reward-guided self-imitation mechanism that encourages the policy to consistently produce high-quality trajectories efficiently, rather than outputs of inconsistent quality, thereby reducing reliance on extensive sampling and post-filtering. During training, we employ a reward-driven curriculum learning paradigm to mitigate inefficient data utility, and goal-agnostic exploration for trajectory augmentation to improve planning robustness. Extensive evaluations on a comprehensive simulation benchmark show that SIDP significantly outperforms previous methods, with real-world experiments confirming its effectiveness across multiple robotic platforms. On Jetson Orin Nano, SIDP delivers a 2.5$\times$ faster inference than the baseline NavDP, i.e., 110ms VS 273ms, enabling efficient real-time deployment.

cs.RO

Legitimizing, Developing, and Sustaining Feminist HCI in East Asia: Challenges and Opportunities

Feminist HCI has been rapidly developing in East Asian contexts in recent years. The region's unique cultural and political backgrounds have contributed valuable, situated knowledge, revealing topics such as localized digital feminism practices, or women's complex navigation among social expectations. However, the very factors that ground these perspectives also create significant survival challenges for researchers in East Asia. These include a scarcity of dedicated funding, the stigma of being perceived as less valuable than productivity-oriented technologies, and the lack of senior researchers and established, resilient communities. Grounded in these challenges and our prior collective practices, we propose this meet-up with two focused goals: (1) to provide a legitimized channel for Feminist HCI researchers to connect and build community, and (2) to facilitate an action-oriented dialogue on how to legitimize, develop, and sustain Feminist HCI in the East Asian context. The website for this meet-up is: https://feminist-hci.github.io/

cs.HC

From Platform Migration to Cultural Integration: the Ingress and Diffusion of #wlw from TikTok to RedNote in Queer Women Communities

Hashtags serve as identity markers and connection tools in online queer communities. Recently, the Western-origin #wlw (women-loving-women) hashtag has risen in the Chinese lesbian community on RedNote, coinciding with user migration triggered by the temporary US TikTok ban. This event provides a unique lens to study cross-cultural hashtag ingress and diffusion through the populations' responsive behaviors in cyber-migration. In this paper, we conducted a two-phase content analysis of 418 #wlw posts from January and April, examining different usage patterns during the hashtag's ingress and diffusion. Results indicate that the successful introduction of #wlw was facilitated by TikTok immigrants' bold importation, both populations' mutual interpretation, and RedNote natives' discussions. In current manifestation of diffusion, #wlw becomes a RedNote-recognized queer hashtag for sharing queer life, and semantically expands to support feminism discourse. Our findings provide empirical insights for enhancing the marginalized communities' cross-cultural communication.

cs.SI

PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration

Researchers frequently need to synthesize their own publications into coherent narratives that demonstrate their scholarly contributions. To suit diverse communication contexts, exploring alternative ways to organize one's work while maintaining coherence is particularly challenging, especially in interdisciplinary fields like HCI where individual researchers' publications may span diverse domains and methodologies. In this paper, we present PaperBridge, a human-AI co-exploration system informed by a formative study and content analysis. PaperBridge assists researchers in exploring diverse perspectives for organizing their publications into coherent narratives. At its core is a bi-directional analysis engine powered by large language models, supporting iterative exploration through both top-down user intent (e.g., determining organization structure) and bottom-up refinement on narrative components (e.g., thematic paper groupings). Our user study (N=12) demonstrated PaperBridge's usability and effectiveness in facilitating the exploration of alternative research narratives. Our findings also provided empirical insights into how interactive systems can scaffold academic communication tasks.

cs.HC

Conversations With The Stressed Body: Facilitating Stress Self-Disclosure Among Adolescent Girls Through An Embodied Approach

Adolescent girls face significant mental health challenges during their transition to adulthood, often experiencing heightened stress from various sources. While various interactive technologies for self-disclosure had been explored to support stress relief, little is known about how to encourage stress-related self-disclosure through an embodied approach. This study presents a co-design workshop centred on Embodied Probes, a series of artefacts and activities incorporating embodied methods and technologies. During the workshop, nine participants aged 15 to 18 engaged with their bodies, expressed bodily sensations through tangible means, and designed embodied prototypes tailored to their personal needs for stress perception and relief. The workshop revealed insights into somatic symptoms, sources, and coping strategies for stress among adolescent girls, as well as how embodied methods can support their stress self-disclosure. This paper contributes to the HCI community by offering design implications on leveraging embodied technologies to support self-disclosure for young women's mental well-being.

cs.HC

Walk in Their Shoes to Navigate Your Own Path: Learning About Procrastination Through A Serious Game

Procrastination, the voluntary delay of tasks despite potential negative consequences, has prompted numerous time and task management interventions in the HCI community. While these interventions have shown promise in addressing specific behaviors, psychological theories suggest that learning about procrastination itself may help individuals develop their own coping strategies and build mental resilience. However, little research has explored how to support this learning process through HCI approaches. We present ProcrastiMate, a text adventure game where players learn about procrastination's causes and experiment with coping strategies by guiding in-game characters in managing relatable scenarios. Our field study with 27 participants revealed that ProcrastiMate facilitated learning and self-reflection while maintaining psychological distance, motivating players to integrate newly acquired knowledge in daily life. This paper contributes empirical insights on leveraging serious games to facilitate learning about procrastination and offers design implications for addressing psychological challenges through HCI approaches.

cs.HC