The Substance III 🧪
某种物质 III 🧪
📷 Nikon F4E
🎞️ Harman Switch Azure (FF)
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Sources: Amazon is in advanced talks to acquire satellite operator Globalstar in a deal that could be announced as soon as Tuesday; GSAT jumps 15% pre-market (Bloomberg)
https://www.bloomberg.com/news/articles/2026-04-14/am…
Digital unterstützte Parkraumkontrolle: Von der Vorbereitung zum Regelbetrieb - #Scancars
von @…
Replaced article(s) found for eess.AS. https://arxiv.org/list/eess.AS/new
[1/1]:
- Unifying Diarization, Separation, and ASR with Multi-Speaker Encoder
Muhammad Shakeel, Yui Sudo, Yifan Peng, Chyi-Jiunn Lin, Shinji Watanabe
https://arxiv.org/abs/2508.20474 https://mastoxiv.page/@arXiv_eessAS_bot/115110974009150613
- CALM: Joint Contextual Acoustic-Linguistic Modeling for Personalization of Multi-Speaker ASR
Muhammad Shakeel, Yosuke Fukumoto, Chikara Maeda, Chyi-Jiunn Lin, Shinji Watanabe
https://arxiv.org/abs/2601.22792 https://mastoxiv.page/@arXiv_eessAS_bot/116000207024295325
- How Much Does Machine Identity Matter in Anomalous Sound Detection at Test Time?
Kevin Wilkinghoff, Keisuke Imoto, Zheng-Hua Tan
https://arxiv.org/abs/2602.16253 https://mastoxiv.page/@arXiv_eessAS_bot/116096185732811365
- LMU-Based Sequential Learning and Posterior Ensemble Fusion for Cross-Domain Infant Cry Classific...
Niloofar Jazaeri, Hilmi R. Dajani, Marco Janeczek, Martin Bouchard
https://arxiv.org/abs/2603.02245 https://mastoxiv.page/@arXiv_eessAS_bot/116169771215037748
- Adapting a Text-to-Audio Model for Room Impulse Response Generation
Kirak Kim, Sungyoung Kim
https://arxiv.org/abs/2603.09708 https://mastoxiv.page/@arXiv_eessAS_bot/116209762413602825
- Repurposing Image Diffusion Models for Training-Free Music Style Transfer on Mel-spectrograms
Heehwan Wang, Joonwoo Kwon, Sooyoung Kim, Jungwoo Seo, Shinjae Yoo, Yuewei Lin, Jiook Cha
https://arxiv.org/abs/2411.15913 https://mastoxiv.page/@arXiv_csSD_bot/113548024475383386
- DeePen: Penetration Testing for Audio Deepfake Detection
M\"uller, Kawa, Stan, Doan, Jung, Choong, Sperl, B\"ottinger
https://arxiv.org/abs/2502.20427 https://mastoxiv.page/@arXiv_csCR_bot/114097333876265997
- Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognition
Yuu Jinnai
https://arxiv.org/abs/2510.19471 https://mastoxiv.page/@arXiv_csCL_bot/115422969877240889
- Aliasing-Free Neural Audio Synthesis
Yicheng Gu, Junan Zhang, Chaoren Wang, Jerry Li, Zhizheng Wu, Lauri Juvela
https://arxiv.org/abs/2512.20211 https://mastoxiv.page/@arXiv_csSD_bot/115773521971327576
- TiCo: Time-Controllable Spoken Dialogue Model
Kai-Wei Chang, Wei-Chih Chen, En-Pei Hu, Hung-yi Lee, James Glass
https://arxiv.org/abs/2603.22267 https://mastoxiv.page/@arXiv_csCL_bot/116283643505371784
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Although both parties have
“strong incentives” to maintain a ceasefire,
the deal is “extremely precarious,”
says Eskandar Sadeghi-Boroujerdi,
professor of international relations of the Middle East at the University of St Andrews in Scotland.
“We’re already seeing it being imperiled as we speak,
with ongoing attacks in Lebanon,
as well as reports of [Iranian] attacks in the Persian Gulf.”
NFL Network: Chargers agree to terms with TE David Njoku https://www.nfl.com/news/nfl-network-chargers-agree-to-terms-with-te-david-njoku
PHEW! Terminé con cinco minutos restantes.
Here's my short essay from my test. It's about AI, and the impact of technology in general. Go easy on me. (Actual proper citations were not needed)
——
La tecnología mšs importante en la sociedad actual es el inteligencia artificial, IA, o el acrónimo inglés, “AI”.
“AI” es una tecnología relativamente nueva. Él aparecí al comienzo del ano 2023 y cambió ršpidamente la manera que los personas en línea buscaban y creaban. Realmente, “AI” no esta inteligente, mejor dicho uno modelo de lenguaje grande, “LLM” en inglés. LLM significa que los ordenadores que les alimentan no usan razón, pero los intentos a predecir una respuesta de una pregunta o mensaje en función de los patrones de palabras y mensajes en les bancos de datos.(1)
La tecnología ha contribuido en gran medida al progreso del sociedad. La tecnología agrícola lo hizo posible para humanidad a crecer y cambiar de nómada a creer asentamientos y eventualmente ciudades mas grandes. La hecha posible a usar recursos del medio ambiente en nos sociedades. Pero la tecnología ha creado grandes problemas también como desigualdad o cambio climštico.
Yo creo que, en la mayoría de situaciones, la tecnología es una fuerza positiva en la sociedad. Las problemas son creado por los personas sin moralidad, a menudo para la acumulación de la riqueza, influencia, y autoridad. Si la población puede mantener la influencia democrštica para reglamentar la tecnología, como la AI, para el beneficio de la población y los individuos, entonces la tecnología puede contribuir a la progresión de la sociedad.
Finalmente, si los individuos son compasivos y respetuosos, la tecnología reflejarš esa también.
1: “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity” #español
The Substance II 🧪
某种物质 II 🧪
📷 Nikon F4E
🎞️ Harman Switch Azure (FF)
If you like my work, Support by buying me a coffee or a roll of film from PayPal https://www.paypal.com/paypalme/ydcdingsite
Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/5]:
- POTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text Translation
Li, Cui, Wang, Ge, Huang, Li, Peng, Lu, Tashi, Wang, Dang
https://arxiv.org/abs/2511.09232 https://mastoxiv.page/@arXiv_csCL_bot/115541846907664054
- Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks
Yunzhe Xu, Zhuosheng Zhang, Zhe Liu
https://arxiv.org/abs/2511.10465 https://mastoxiv.page/@arXiv_csCL_bot/115547607561282911
- $\pi$-Attention: Periodic Sparse Transformers for Efficient Long-Context Modeling
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.10696 https://mastoxiv.page/@arXiv_csCL_bot/115564418836654965
- Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performanc...
Zijin Su, Huanzhu Lyu, Yuren Niu, Yiming Liu
https://arxiv.org/abs/2511.14073 https://mastoxiv.page/@arXiv_csCL_bot/115575715073023141
- HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning
Alexis Correa-Guill\'en, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2511.15355 https://mastoxiv.page/@arXiv_csCL_bot/115581410328165116
- Towards Hyper-Efficient RAG Systems in VecDBs: Distributed Parallel Multi-Resolution Vector Search
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.16681 https://mastoxiv.page/@arXiv_csCL_bot/115603508442305146
- Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Transla...
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, Marika Borovikova, Dage S\"arg, Kairit Sirts
https://arxiv.org/abs/2511.17290 https://mastoxiv.page/@arXiv_csCL_bot/115604083224487885
- A Systematic Study of In-the-Wild Model Merging for Large Language Models
O\u{g}uz Ka\u{g}an Hitit, Leander Girrbach, Zeynep Akata
https://arxiv.org/abs/2511.21437 https://mastoxiv.page/@arXiv_csCL_bot/115621178703846052
- CREST: Universal Safety Guardrails Through Cluster-Guided Cross-Lingual Transfer
Lavish Bansal, Naman Mishra
https://arxiv.org/abs/2512.02711 https://mastoxiv.page/@arXiv_csCL_bot/115655090475535157
- Multilingual Medical Reasoning for Question Answering with Large Language Models
Pietro Ferrazzi, Aitor Soroa, Rodrigo Agerri
https://arxiv.org/abs/2512.05658 https://mastoxiv.page/@arXiv_csCL_bot/115683267711014189
- OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Convers...
Albrecht, Lehmann, Poltermann, Rudolph, Steigerwald, Stieler
https://arxiv.org/abs/2512.09804 https://mastoxiv.page/@arXiv_csCL_bot/115700409397020978
- Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, an...
Hanyu Cai, Binqi Shen, Lier Jin, Lan Hu, Xiaojing Fan
https://arxiv.org/abs/2512.12812 https://mastoxiv.page/@arXiv_csCL_bot/115729149622659403
- Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Ovalle, Ross, Ruder, Williams, Ullrich, Ibrahim, Sagun
https://arxiv.org/abs/2512.22712 https://mastoxiv.page/@arXiv_csCL_bot/115808161882146194
- Activation Steering for Masked Diffusion Language Models
Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit Levi, Raz Lapid
https://arxiv.org/abs/2512.24143 https://mastoxiv.page/@arXiv_csCL_bot/115819533211103315
- JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese L...
Liu, Li, Niu, Zhang, Xun, Hou, Wang, Iwasawa, Matsuo, Hatakeyama-Sato
https://arxiv.org/abs/2601.01627 https://mastoxiv.page/@arXiv_csCL_bot/115847901607405421
- FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Dassen, Kotula, Murray, Yates, Lawrie, Kayi, Mayfield, Duh
https://arxiv.org/abs/2601.05866 https://mastoxiv.page/@arXiv_csCL_bot/115881545684182376
- {\dag}DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
Zabir Al Nazi, Shubhashis Roy Dipta, Sudipta Kar
https://arxiv.org/abs/2601.06853 https://mastoxiv.page/@arXiv_csCL_bot/115887753245730019
- Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Stephen Gadd
https://arxiv.org/abs/2601.06932 https://mastoxiv.page/@arXiv_csCL_bot/115887767008671765
- LLMs versus the Halting Problem: Revisiting Program Termination Prediction
Sultan, Armengol-Estape, Kesseli, Vanegue, Shahaf, Adi, O'Hearn
https://arxiv.org/abs/2601.18987 https://mastoxiv.page/@arXiv_csCL_bot/115972010510378715
- MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu
https://arxiv.org/abs/2601.20451 https://mastoxiv.page/@arXiv_csCL_bot/115977891530875024
toXiv_bot_toot
The Substance 🧪
某种物质 🧪
📷 Nikon F4E
🎞️ Harman Switch Azure (FF)
If you like my work, Support by buying me a coffee or a roll of film from PayPal https://www.paypal.com/paypalme/ydcdingsite