Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions underlying secondary pollutant formation. Purely data-driven models often suffer from long-horizon drift and lack physical consistency, while existing physics-informed appr...
Kien Le Trung, Tung Kieu, Dinh Duc Nha Nguyen et al.· 0 citations
Existing human-centred XAI research predominantly evaluates explanations after they have been generated. However, this fails to provide actionable insights into improving accessibility. This study incorporates human-based feature understandability into feature selection to improve the generation of human-centred explan...
Nicola Rossberg, Bennett Kleinberg, Barry O'Sullivan et al.· 0 citations
With the advancement in language modeling, research on adversarial images has recently shifted from image classifiers to vision-language models (VLMs). Despite the new, text-prompt-driven nature of VLMs, we find that existing VLM adversaries have largely overlooked the dynamics of text prompts. In a typical use case, a...
Shun-Yuan Bai, Yu-Chen Ren, Le Yang et al.· 0 citations
Processing multilingual text requires both identifying a broad range of languages and distinguishing the language of each token in inputs containing multiple languages. We introduce MixLID, a token-level language identification model supporting 111 language-script combinations. MixLID follows a two-stage training proce...
Seongtae Hong, Youngjoon Jang, Seungyoon Lee et al.· 0 citations
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A new framework of multimodal seizure classification integrating the heterogeneous EEG and iEEG recordings from different subjects and sources is presented, using the EEGNet-Vision Transformer as the feature extraction and classification network to learn the local discriminative patterns as well as global contextual in...
R. Sundaram, M. Jarwar, M. Uma et al.· 0 citations
Vision-Language-Action models (VLAs) have achieved high success rates on familiar manipulation tasks, yet it remains unclear whether such scores reflect genuine zero-shot generalization and perturbation robustness. Existing evaluation frameworks provide limited capability-level diagnosis and combinatorial perturbation...
Jun Xiao, Rui Ye, Dong-Run Cao et al.· 0 citations
Feature caching has become a mainstream training-free strategy for accelerating video diffusion models by reusing intermediate outputs across denoising steps. However, existing adaptive methods rely on heuristic difference measures misaligned with actual generation quality, employ a single global threshold that ignores...
Ji-Yue Jiang, Zhi-Yu Huo, Yu-Han Chen et al.· 0 citations
We present PatTransBench, a 12,000-item Chinese-English/Japanese/Korean patent machine translation (PatMT) benchmark with a four-dimensional evaluation protocol. The benchmark comprises 6,000 short-text (sentence/claim) and 6,000 long-text (paragraph) pairs, evenly split across three language pairs and both translation...
Developing reliable predictive models for multi-physics systems often forces a compromise between computationally demanding physical simulators and data-hungry, opaque machine learning (ML) algorithms. While incorporating dimensional analysis into directed computation graphs offers a structurally sound alternative to e...
Akshay Dhalpe, Arnab Chattopadhyay, S. B. Balani et al.· 0 citations
Generative Social Simulation (GSS) leverages Large Language Models (LLMs) to create sophisticated personas that define agents with demographics, emotions, and political opinions. While prior work shows that personas compress outputs into stereotypical caricatures, there is no comprehensive study of how these caricature...
Dimitris Michailidis, Petter Törnberg, Fernando P. Santos· 0 citations
Speculative Recursive Self-Improvement (SpecRSI) is introduced, which drafts executable successor agents before their predecessors are fully evaluated, while requiring complete verification before adoption.
G GrowRL is proposed, an RL method that organizes learned updates into compact computational pathways through structural growth, and shows competitive mathematical reasoning and out-of-distribution performance with a small number of trainable parameters.
