arXiv:2505.09558v2 Announce Type: replace-cross Abstract: End-to-end spoken dialogue models such as GPT-4o-audio have recently garnered significant attention in the speech domain. However, the evaluation of spoken dialogue models’ conversational performance has largely been overlooked. This is primarily due to the…
arXiv:2509.18382v1 Announce Type: new Abstract: Test-time compute scaling has demonstrated the ability to improve the performance of reasoning language models by generating longer chain-of-thought (CoT) sequences. However, this increase in performance comes with a significant increase in computational cost. In…
arXiv:2502.13329v2 Announce Type: replace-cross Abstract: The text produced by language models (LMs) can exhibit specific `behaviors,’ such as a failure to follow alignment training, that we hope to detect and react to during deployment. Identifying these behaviors can often only…
arXiv:2509.18234v1 Announce Type: new Abstract: Large frontier models like GPT-5 now achieve top scores on medical benchmarks. But our stress tests tell a different story. Leading systems often guess correctly even when key inputs like images are removed, flip answers…
arXiv:2408.08182v4 Announce Type: replace-cross Abstract: People with Parkinson’s Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease progresses. Existing clinical rating tools are not capable of capturing hour-by-hour variations of PD symptoms,…
arXiv:2509.18230v1 Announce Type: new Abstract: Controlling desktop applications via software remains a fundamental yet under-served problem. Existing multi-modal large language models (MLLMs) ingest screenshots and task instructions to generate keystrokes and mouse events, but they suffer from prohibitive inference latency,…
arXiv:2507.03616v2 Announce Type: replace Abstract: Multi-agent systems (MAS) have emerged as a powerful paradigm for orchestrating large language models (LLMs) and specialized tools to collaboratively address complex tasks. However, existing MAS frameworks often require manual workflow configuration and lack native…
arXiv:2509.18229v1 Announce Type: new Abstract: Generative AI, and specifically GPT, can produce a remarkable solution to a mechanical engineering analysis problem – but also, on occasion, a flawed solution. For example, an elementary mechanics problem is solved flawlessly in one…
arXiv:2509.19270v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) for low-resource languages like Slovak is hindered by the scarcity of training data. To address this, we introduce SloPalSpeech, a new, large-scale Slovak ASR dataset containing 2,806 hours of speech from…
arXiv:2509.18226v1 Announce Type: new Abstract: Personalized recipe recommendation faces challenges in handling fuzzy user intent, ensuring semantic accuracy, and providing sufficient detail coverage. We propose ChefMind, a hybrid architecture combining Chain of Exploration (CoE), Knowledge Graph (KG), Retrieval-Augmented Generation (RAG),…
