Hyper-LLaVA introduces a hyperbolic uncertainty‑aware, modality‑balanced routing mechanism for multimodal continual instruction tuning. It improves intra‑modality task matching by evaluating sample‑to‑task distribution similarity in hyperbolic space and mitigates unreliable modality influence by quantifying task‑matching ambiguity to adaptively balance across modalities. The approach achieves significant performance gains over existing methods.
By Kunlun Xu, Yanqin Zhang, Wenwen Qiang, Jiahuan Zhou
arXiv:2609.13150v1 Announce Type: cross
Abstract: Reference-free quality predictors such as UTMOS, DNSMOS and SCOREQ are the de facto automatic evaluators for text-to-speech (TTS) and are increasingl...
By Antonis Asonitis, Juan Pablo Zuluaga Gomez, Francesco Verdini, Aref Farhadipour, Marzieh Razavi, Pierre-Edouard Honnet, Vijeta Avijeet
arXiv:2609.13225v1 Announce Type: cross
Abstract: Benchmarks agree that vision-language models reason poorly about low-level manipulation, but an aggregate accuracy score does not say which step fail...
By Sarthak Sattigeri
arXiv:2609.13277v1 Announce Type: cross
Abstract: Lunar orbital missions, such as Lunar Reconnaissance Orbiter, Kaguya/SELENE, Gravity Recovery and Interior Laboratory, and Lunar Prospector, among ot...
By Himanshu Patil, Gabby Nyirjesy, Rachel A. Slank, Vishal Gaur, Daniela Szwarcman, Paolo Fraccaro, Nikolaos Dionelis, Michael K. Barker, Andrew Annex, Vishnu Viswanathan, Zachary Morse, Ethan I. Schaefer, Hiyam Debary, Ankur Kumar, Rohit Lal, Geoffrey Dawson, Campbell Watson, Rebekah I. Dawson-Rigas, Manil Maskey, Juan Bernab\'e-Moreno, Rahul Ramachandran, Sujit Roy
arXiv:2609.13868v1 Announce Type: cross
Abstract: Earth-observation (EO) foundation models have become exceptionally effective at learning se mantic, high-dimensional geospatial embeddings, while mod...
By Rajiv Ranjan
arXiv:2609.14146v1 Announce Type: cross
Abstract: Vision-language-action (VLA) deployment can reduce inference latency while changing closed-loop task behavior. We evaluate HuggingFaceVLA/smolvla_lib...
By Rafiqul Islam
arXiv:2609.14261v1 Announce Type: cross
Abstract: Recent robot learning paradigms increasingly rely on large offline datasets of robotic interactions to train control policies. Expressive generative...
By Prajwal Koirala, Mark Campbell
arXiv:2609.14764v1 Announce Type: cross
Abstract: Early detection of cognitive decline from speech offers a scalable and non-invasive alternative to conventional clinical assessment. Verbal fluency t...
By Madhurananda Pahar, Caitlin Illingworth, Dorota Braun, Daniel Blackburn, Heidi Christensen
ReH-FUSE is a reliability‑aware hierarchical fusion framework for multimodal emotion recognition in conversation. It uses a decision‑level router to first compare the relative preference between text and audio, then balances this unimodal mixture with a cross‑modal expert, thereby separating unimodal competition from cross‑modal selection. Experiments on IEMOCAP and MELD show that ReH-FUSE achieves state‑of‑the‑art weighted and macro F1 scores, and ablation studies confirm that learned routing outperforms uniform expert averaging and benefits from cross‑modal interaction.
By Guan-Hua Wen, Hou-Chiang Tseng, Kuan-Yu Chen
arXiv:2604.10632v2 Announce Type: replace-cross
Abstract: Music and food traditions are both intangible cultural heritage, and the links between them, how a sound can make a taste seem sweeter or mor...
By Matteo Spanio, Valentina Frezzato, Antonio Rod\`a
arXiv:2609.13151v1 Announce Type: new
Abstract: Leading multilingual speech recognition models like Whisper transcribe diverse, low-resource languages without language-specific training but are compu...
By Dylan Luke Holyoak
arXiv:2609.13794v1 Announce Type: new
Abstract: Detecting harmful memes is critical for maintaining safe online communities. However, harmful intent is often implicit, arising from visual-textual inc...
By Hanling Wang, Chenlong Wei, Yingjuan Li, Di Wu, Yuchao Zhang, Xiaohui Zhu, Yao Zhu
arXiv:2609.14207v1 Announce Type: new
Abstract: We propose to finetune vision-language models to generate more pragmatically optimal referring expressions by transforming observations of incremental...
By T\'ea Wright, Alane Suhr
arXiv:2609.14302v1 Announce Type: new
Abstract: Can financial vision-language models (VLMs) turn chart evidence into reliable action recommendations? Existing hallucination evaluations are mostly cla...
By Xiaoya Wang, Yutong Xu, Junjie Wang
arXiv:2609.15152v1 Announce Type: cross
Abstract: Multimodal embedding models encode heterogeneous inputs into a shared embedding space, enabling efficient similarity computation across modalities an...
By Yanping Li, Wei Zhou, Yawen Liu, Yibo Wang, Ke Zhu, Guangda Huzhang, Qing-Guo Chen, Zhao Xu, Jun Zhang, Wei Wei
arXiv:2609.14817v1 Announce Type: new
Abstract: In Yor\`ub\'a, pitch alone separates \d{o}k\d{o} (husband, Mid), \d{o}k\d{\`o} (vehicle, Low), and \d{o}k\d{\'o} (hoe, High) -- the diacritics ARE the...
By Moses Daudu, Adeola Enitan Bamidele, Honor-Jesus Bezaleel
arXiv:2609.14967v1 Announce Type: new
Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (...
By Yahya Mohamed Elnawasany
arXiv:2609.14991v1 Announce Type: new
Abstract: Open Thai automatic speech recognition (ASR) is dominated by offline, Whisper-based models that read the whole utterance before transcribing, ruling ou...
By Warit Sirichotedumrong, Tanawin Samutsin, Shah Faisal Wani, Sittipong Sripaisarnmongkol, Kunat Pipatanakul
arXiv:2609.15743v1 Announce Type: new
Abstract: Automatic speech recognition (ASR) systems, trained on paired speech-text data, have been improved by leveraging language models (LMs) trained on text-...
By Hayato Futami, Tatsuya Kawahara
arXiv:2609.13237v1 Announce Type: cross
Abstract: Orthodontic report generation from intraoral data is normally cast as multimodal captioning, yet the released Bite2Text scan pairs are supplied alrea...
By Ajo Babu George, Govind Arun, Sidharth N Krishna, Uma Ranjan