The Tech Gazette

Context caching is widely adopted to reduce the dominant prefill cost for long prompts across various large language model (LLM) applications. Recently, position-independent caching (PIC) has emerged to improve KV cache reuse beyond strict prefix matching. However, the required K…

For widespread deployment of autonomous driving systems (ADS), perception robustness plays a fundamental role. However, maintaining robust perception performance remains a significant challenge, especially under occlusion-rich conditions, known as blind-spot driving scenarios. In…

Fully Homomorphic Encryption (FHE) has the potential to substantially improve privacy and security by enabling computation directly on encrypted data. This is especially true in deep learning, as many popular user services today are powered by neural networks in the cloud. Beyond…

Session-based recommendation (SBR) predicts the next item based on anonymous sessions. Traditional SBR explores user intents based on ID collaborations or auxiliary content. To further alleviate data sparsity and cold-start issues, recent Multimodal SBR (MSBR) methods utilize sim…

Sequential recommendation generates personalized item rankings by estimating latent user-preference distributions from historical interactions. Although Diffusion Models (DMs) have gained prominence due to their exceptional capacity to capture complex distributions, current DM-ba…

Agentic and multi-agent AI systems are increasingly deployed as part of operational systems, introducing autonomous planning, delegation, persistent memory, tool use, and inter-agent coordination into data-driven decision making. These architectural properties challenge prevailin…

The ancient art of Traditional Chinese Medicine (TCM) is distinguished by its extensive annals of utilizing nature's botanical emissaries to ameliorate various pathological conditions. TCM diagnosis and treatment exhibit a pronounced degree of personalization and an organically h…

Recommender systems (RS) increasingly mediate what users see, buy, and believe, making them attractive targets for malicious manipulation. As RS have progressed from traditional collaborative filtering to deep learning and, most recently, LLM-driven designs, the landscape has co-…

Large language models have shown strong potential in automating code editing (CE) tasks, yet most existing systems rely on a fixed CE strategy (i.e., one-step, search-replace, and plan-apply) across diverse scenarios. In practice, CE tasks vary widely in code context, edit locali…

Conventional forecasting methods are trained end-to-end on unimodal time series, which limits their ability to exploit textual information and undermines their generalization in data-scarce scenarios. Recently, large language models (LLMs) and time series foundation models (TSFMs…

This study presents a comprehensive multi-level analysis of the NVIDIA Hopper GPU architecture, focusing on its performance characteristics and novel features. We benchmark Hopper’s memory subsystem, highlighting improvements in the L2 partitioned cache and global memory access c…

Gamification improves employee engagement and productivity, but raises concerns about how data is collected, processed, stored, and used. Consequently, analyzing privacy concerns in gamification is complex and time-consuming. Large Language Models (LLMs) are promising because the…

Global connectivity has increased societal diversity worldwide, fostering growth and dispelling negative stereotypes. However, ensuring equality remains challenging, with some groups favoured and others facing unequal opportunities. The evolution of Artificial Intelligence (AI) p…

Although LLMs have been widely adopted for creative content generation, a single-pass process often struggles to produce high-quality long narratives. How to effectively revise and improve long narrative scripts like scriptwriters remains a significant challenge, as it demands a…

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI’s ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in high consumption of computational, memory…

Tabular data remains one of the most challenging modalities for deep learning due to its heterogeneity, lack of spatial or sequential inductive bias, and small-sample regimes. Key complexities include mixed feature types, high-cardinality categoricals, missing or sparse entries,…

Business logic bugs violate intended business semantics and are particularly prevalent in enterprise software. Yet most existing unit test generation techniques are code-centric, making such bugs difficult to expose. We present SeGa, a semantics-driven unit test generation techni…

We propose CMod, an economic model for analyzing the economic security of decentralized finance (DeFi) smart contract code. CMod defines the notions of economic value, intended-return conditions, and unintended single-transaction return, and reasons about economic security by pro…

Multi-modal recommender system (MRS) has emerged as a key information retrieval technology, widely adopted to enhance various web platforms. However, three interrelated challenges remain insufficiently explored: (1) noisy multi-modal content, (2) noisy user feedback, and (3) misa…

Recommendation throughout the cold-start period remains a challenge in recommender systems. Strictly cold entities (users/items) have no interactions, while warm-up entities only have a few unreliable interactions. Strict cold-start methods typically overlook warm-up entities, wh…

Modern REST API testing faces a critical challenge in defining reliable test oracles, particularly in agile industrial environments where formal specifications (e.g., OpenAPI) are frequently missing or outdated, and historical execution logs are unavailable for newly deployed end…

Vulnerability reports play a critical role in software repair, with Proof-of-Concept (PoC) tests serving as one of their most essential components. PoC tests enable software developers to reliably reproduce reported vulnerabilities and subsequently deploy patches. However, genera…

User Stories are key artifacts in Requirement and Software Engineering. Despite their wide adoption, their writing in industrial contexts tends to diverge from the principles initially stated in Agile methodologies. In this context, sets of metrics such as INVEST or QUS emerged t…

Relational tables widely exist in enterprise data lakes and repositories, yet they often lack semantic context such as column types and relationships, creating a bottleneck for automated data management. Semantic Table Annotation, comprising tasks like Column Type Annotation (CTA…

In recommender systems, user feedback typically follows a long-tail distribution, which leads many recommendation algorithms to exacerbate popularity bias by disproportionately favoring popular items. To mitigate this issue, recent studies have employed Inverse Propensity Scoring…

Nature Computational Science, Published online: 12 October 2026; doi:10.1038/s43588-026-01045-2 Researchers show that large language models cannot learn from spatial coordinates regardless of model or data scale. Specialized geometric neural networks consistently outperform langu…

With the widespread application of trajectory data in areas such as traffic management and route planning, efficiently computing trajectory similarity for fast retrieval has become a critical challenge. Existing methods for trajectory similarity measurement often face issues of l…

The rapid growth of scientific publications makes scholarly taxonomies quickly obsolete. We study taxonomy maintenance in the wild, a new problem that moves beyond static construction by continuously adapting taxonomies to evolving scholarly repositories, such as arXiv, for a giv…

When written work no longer shows who did the thinking, voice AI can bring back the oral exam at scale.

Community search (CS) is a fundamental problem in graph analysis, which aims to identify a query-dependent cohesive subgraph that satisfies a specific community model and contains the given query vertices. While numerous CS approaches have been proposed, including non-learning-ba…