· ai
[Paper] Self-Paced Learning for Images of Antinuclear Antibodies
Antinuclear antibody (ANA) testing is a crucial method for diagnosing autoimmune disorders, including lupus, Sjögren's syndrome, and scleroderma. Despite its im...
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- · ai
[Paper] Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation
Unlike text, speech conveys information about the speaker, such as gender, through acoustic cues like pitch. This gives rise to modality-specific bias concerns....
- · ai
[Paper] Mechanistic Interpretability for Transformer-based Time Series Classification
Transformer-based models have become state-of-the-art tools in various machine learning tasks, including time series classification, yet their complexity makes ...
- · ai
[Paper] IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference
Deploying Transformer models on edge devices is limited by latency and energy budgets. While INT8 quantization effectively accelerates the primary matrix multip...
- · ai
[Paper] Tool-RoCo: An Agent-as-Tool Self-organization Large Language Model Benchmark in Multi-robot Cooperation
This study proposes Tool-RoCo, a novel benchmark for evaluating large language models (LLMs) in long-term multi-agent cooperation based on RoCo, a multi-robot c...
- · ai
[Paper] Lost in Time? A Meta-Learning Framework for Time-Shift-Tolerant Physiological Signal Transformation
Translating non-invasive signals such as photoplethysmography (PPG) and ballistocardiography (BCG) into clinically meaningful signals like arterial blood pressu...
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[Paper] Merge and Bound: Direct Manipulations on Weights for Class Incremental Learning
We present a novel training approach, named Merge-and-Bound (M&B) for Class Incremental Learning (CIL), which directly manipulates model weights in the para...
- · ai
[Paper] MobileI2V: Fast and High-Resolution Image-to-Video on Mobile Devices
Recently, video generation has witnessed rapid advancements, drawing increasing attention to image-to-video (I2V) synthesis on mobile devices. However, the subs...
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[Paper] Hierarchical Ranking Neural Network for Long Document Readability Assessment
Readability assessment aims to evaluate the reading difficulty of a text. In recent years, while deep learning technology has been gradually applied to readabil...
- · ai
[Paper] SpatialBench: Benchmarking Multimodal Large Language Models for Spatial Cognition
Spatial cognition is fundamental to real-world multimodal intelligence, allowing models to effectively interact with the physical environment. While multimodal ...
- · ai
[Paper] Mean-Field Limits for Two-Layer Neural Networks Trained with Consensus-Based Optimization
We study two-layer neural networks and train these with a particle-based method called consensus-based optimization (CBO). We compare the performance of CBO aga...
- · ai
[Paper] MADRA: Multi-Agent Debate for Risk-Aware Embodied Planning
Ensuring the safety of embodied AI agents during task planning is critical for real-world deployment, especially in household environments where dangerous instr...