Tootfinder

Googles kleines Sprachlabor: Fremdsprachen lernen mit Little Language Lessons
KI trifft Sprachtraining: Wir haben die „Little Language Lessons“ von Google getestet – taugt das Tool für schnelles, effektives Lernen einer Fremdsprache?

@… Indeed, and before everything pivoted to statistics, it looked like it could be equal parts linguistics and engineering. But with the rise of statistics and “language independent” methods, any interest in language rapidly disappeared.

@… Indeed, and before everything pivoted to statistics, it looked like it could be equal parts linguistics and engineering. But with the rise of statistics and “language independent” methods, any interest in language rapidly disappeared.

Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion
Chunlong Xie, Jialing He, Shangwei Guo, Jiacheng Wang, Shudong Zhang, Tianwei Zhang, Tao Xiang
https://arxiv.org/abs/2505.23266

Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion
We present Adversarial Object Fusion (AdvOF), a novel attack framework targeting vision-and-language navigation (VLN) agents in service-oriented environments by generating adversarial 3D objects. While foundational models like Large Language Models (LLMs) and Vision Language Models (VLMs) have enhanced service-oriented navigation systems through improved perception and decision-making, their integration introduces vulnerabilities in mission-critical service workflows. Existing adversarial attac…

A Tool for Generating Exceptional Behavior Tests With Large Language Models
Linghan Zhong, Samuel Yuan, Jiyang Zhang, Yu Liu, Pengyu Nie, Junyi Jessy Li, Milos Gligoric
https://arxiv.org/abs/2505.22818

A Tool for Generating Exceptional Behavior Tests With Large Language Models
Exceptional behavior tests (EBTs) are crucial in software development for verifying that code correctly handles unwanted events and throws appropriate exceptions. However, prior research has shown that developers often prioritize testing "happy paths", e.g., paths without unwanted events over exceptional scenarios. We present exLong, a framework that automatically generates EBTs to address this gap. exLong leverages a large language model (LLM) fine-tuned from CodeLlama and incorporates reasoni…

This https://arxiv.org/abs/2505.21432 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Hume: Introducing System-2 Thinking in Visual-Language-Action Model
Humans practice slow thinking before performing actual actions when handling complex tasks in the physical world. This thinking paradigm, recently, has achieved remarkable advancement in boosting Large Language Models (LLMs) to solve complex tasks in digital domains. However, the potential of slow thinking remains largely unexplored for robotic foundation models interacting with the physical world. In this work, we propose Hume: a dual-system Vision-Language-Action (VLA) model with value-guided…

Can Large Language Models Trigger a Paradigm Shift in Travel Behavior Modeling? Experiences with Modeling Travel Satisfaction
Pengfei Xu, Donggen Wang
https://arxiv.org/abs/2505.23262

Can Large Language Models Trigger a Paradigm Shift in Travel Behavior Modeling? Experiences with Modeling Travel Satisfaction
As a specific domain of subjective well-being, travel satisfaction has attracted much research attention recently. Previous studies primarily use statistical models and, more recently, machine learning models to explore the determinants of travel satisfaction. Both approaches require data from sufficient sample sizes and correct prior statistical assumptions. The emergence of Large Language Models (LLMs) offers a new modeling approach that can overcome the shortcomings of the existing methods. …

@… I very much agree with many of your points, and I’m glad that I no longer work in CL—which had already become NLP a long time ago, and is now by many considered “a subfield of ML.”
I think the problem started when computational linguistics and linguistics split into separate disciplines: one less and less interested in language, the other less…

@… I very much agree with many of your points, and I’m glad that I no longer work in CL—which had already become NLP a long time ago, and is now by many considered “a subfield of ML.”
I think the problem started when computational linguistics and linguistics split into separate disciplines: one less and less interested in language, the other less…

Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models
Zenghui Yuan, Yangming Xu, Jiawen Shi, Pan Zhou, Lichao Sun
https://arxiv.org/abs/2505.23561

Merge Hijacking: Backdoor Attacks to Model Merging of Large Language Models
Model merging for Large Language Models (LLMs) directly fuses the parameters of different models finetuned on various tasks, creating a unified model for multi-domain tasks. However, due to potential vulnerabilities in models available on open-source platforms, model merging is susceptible to backdoor attacks. In this paper, we propose Merge Hijacking, the first backdoor attack targeting model merging in LLMs. The attacker constructs a malicious upload model and releases it. Once a victim user …