arXiv:2510.20327v1 Announce Type: cross Abstract: With the growing demand for safeguarding sensitive user information in recommender systems, recommendation attribute unlearning is receiving increasing attention. Existing studies predominantly focus on single-attribute unlearning. However, privacy protection requirements in the real world often involve multiple sensitive attributes and are dynamic. Existing single-attribute unlearning methods cannot meet these real-world […]
Learning Modular Exponentiation with Transformers
arXiv:2506.23679v2 Announce Type: replace-cross Abstract: Modular exponentiation is crucial to number theory and cryptography, yet remains largely unexplored from a mechanistic interpretability standpoint. We train a 4-layer encoder-decoder Transformer model to perform this operation and investigate the emergence of numerical reasoning during training. Utilizing principled sampling strategies, PCA-based embedding analysis, and activation patching, we examine […]
VLSP 2025 MLQA-TSR Challenge: Vietnamese Multimodal Legal Question Answering on Traffic Sign Regulation
arXiv:2510.20381v1 Announce Type: cross Abstract: This paper presents the VLSP 2025 MLQA-TSR – the multimodal legal question answering on traffic sign regulation shared task at VLSP 2025. VLSP 2025 MLQA-TSR comprises two subtasks: multimodal legal retrieval and multimodal question answering. The goal is to advance research on Vietnamese multimodal legal text processing and to provide […]
Advancing Drug Development Through Strategic Cell Line and Compound Selection Using Drug Response Profiles
arXiv:2510.19874v1 Announce Type: new Abstract: Early identification of sensitive cancer cell lines is essential for accelerating biomarker discovery and elucidating drug mechanism of action. Given the efficiency and low cost of small-scale drug screens relative to extensive omics profiling, we compared drug-response panel (DRP) descriptors against omics features for predictive capacity using gradient boosting tree […]
Transferable Black-Box One-Shot Forging of Watermarks via Image Preference Models
arXiv:2510.20468v1 Announce Type: cross Abstract: Recent years have seen a surge in interest in digital content watermarking techniques, driven by the proliferation of generative models and increased legal pressure. With an ever-growing percentage of AI-generated content available online, watermarking plays an increasingly important role in ensuring content authenticity and attribution at scale. There have been […]
Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data
arXiv:2510.06377v2 Announce Type: replace-cross Abstract: Pretrained transformers readily adapt to new sequence modeling tasks via zero-shot prompting, but relational domains still lack architectures that transfer across datasets and tasks. The core challenge is the diversity of relational data, with varying heterogeneous schemas, graph structures and functional dependencies. In this paper, we present the Relational Transformer […]
ARC-Encoder: learning compressed text representations for large language models
arXiv:2510.20535v1 Announce Type: cross Abstract: Recent techniques such as retrieval-augmented generation or chain-of-thought reasoning have led to longer contexts and increased inference costs. Context compression techniques can reduce these costs, but the most effective approaches require fine-tuning the target model or even modifying its architecture. This can degrade its general abilities when not used for […]
Compressing Biology: Evaluating the Stable Diffusion VAE for Phenotypic Drug Discovery
arXiv:2510.19887v1 Announce Type: new Abstract: High-throughput phenotypic screens generate vast microscopy image datasets that push the limits of generative models due to their large dimensionality. Despite the growing popularity of general-purpose models trained on natural images for microscopy data analysis, their suitability in this domain has not been quantitatively demonstrated. We present the first systematic […]
Resounding Acoustic Fields with Reciprocity
arXiv:2510.20602v1 Announce Type: cross Abstract: Achieving immersive auditory experiences in virtual environments requires flexible sound modeling that supports dynamic source positions. In this paper, we introduce a task called resounding, which aims to estimate room impulse responses at arbitrary emitter location from a sparse set of measured emitter positions, analogous to the relighting problem in […]
Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM Conversations
arXiv:2510.20743v1 Announce Type: cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations with implicit non-verbal context. The system integrates a commercial facial expression recognition service to capture users’ emotional cues and embeds them as contextual signals during prompting. Unlike traditional multimodal interfaces, empathic prompting […]