Customer calls contain far more than words. They carry emotional signals that reveal satisfaction, frustration, urgency and trust. Call sentiment analysis uses natural language processing (NLP) to surface those signals at scale, turning raw conversations into actionable intelligence. What Call Sentiment Analysis Actually Measures Call sentiment analysis evaluates the emotional tone expressed in customer interactions, typically after speech has been converted to text using automatic speech recognition (ASR). Sentiment signals often fall into three broad categories: n Polarity: […]

Ver mais

arXiv:2601.03360v1 Announce Type: new Abstract: Continuous-time state estimation has been shown to be an effective means of (i) handling asynchronous and high-rate measurements, (ii) introducing smoothness to the estimate, (iii) post hoc querying the estimate at times other than those of the measurements, and (iv) addressing certain observability issues related to scanning-while-moving sensors. A popular means of representing the trajectory in continuous time is via a Gaussian process (GP) prior, with the prior’s mean and covariance functions generated […]

Ver mais

Slang interpretation has been a challenging downstream task for Large Language Models (LLMs) as the expressions are inherently embedded in contextual, cultural, and linguistic frameworks. In the absence of domain-specific training data, it is difficult for LLMs to accurately interpret slang meaning based on lexical information. This paper attempts to investigate the challenges of slang inference using large LLMs and presents a greedy search-guided chain-of-thought framework for slang interpretation. Through our experiments, we conclude that the model size […]

Ver mais

Clark argues that mind, body, and world are inseparable partners in shaping experience. Perception isn’t about representing a fixed reality but about acting within it—guided by our bodies, tools, and culture. From prosthetic limbs to language itself, humans continuously rebuild their environments and, in doing so, reinvent their own minds through a dance of “profound embodiment.”

Ver mais

Hi! I’m trying to understand Bayesian physics-informed neural networks (PINNs). I have a relatively solid understanding of standard PINNs, but I’m confused about what changes when they are made Bayesian. Specifically: Which components are treated probabilistically? Is uncertainty placed only on the neural network parameters (weights and biases), or also on the data, boundary/initial conditions, or physical parameters? Or does this depend on the specific use case? Or model developed? I’d appreciate any intuition or references that clarify […]

Ver mais

arXiv:2601.04286v1 Announce Type: new Abstract: Objective: Stroke is one of the leading causes of disabilities. One promising approach is to extend the rehabilitation with self-initiated robot-assisted movement therapy. To enable this, it is required to detect the patient’s intention to move to trigger the assistance of a robotic device. This intention to move can be detected from human surface electroencephalography (EEG) signals; however, it is particularly challenging to decode when classifications are performed online and asynchronously. In this […]

Ver mais

arXiv:2601.12224v1 Announce Type: new Abstract: Enabling intuitive, language-driven interaction with surgical scenes is a critical step toward intelligent operating rooms and autonomous surgical robotic assistance. However, the task of referring segmentation, localizing surgical instruments based on natural language descriptions, remains underexplored in surgical videos, with existing approaches struggling to generalize due to reliance on static visual cues and predefined instrument names. In this work, we introduce SurgRef, a novel motion-guided framework that grounds free-form language expressions in instrument […]

Ver mais