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We describe a variant of Child-Sum Tree-LSTM deep neural network (Tai et al, 2015) fine-tuned for working with dependency trees and morphologically rich languages using the example of Polish. Fine-tuning included applying a custom…
This paper introduces the Contextual Evaluation Model (CEM), a novel method for knowledge representation and manipulation. The CEM differs from existing models in that it integrates facts, patterns and sequences into a single contextual…
This is the Proceedings of NIPS 2017 Symposium on Interpretable Machine Learning, held in Long Beach, California, USA on December 7, 2017
Spatial expressions in situated communication can be ambiguous, as their meanings vary depending on the frames of reference (FoR) adopted by speakers and listeners. While spatial language understanding and reasoning by vision-language…
These proceedings contain the papers presented at the 10th International Workshop on Automated Specification and Verification of Web Systems (WWV 2014), which was held on 18 July 2014 in Vienna, Austria, as a satellite workshop of the…
In recent years, cross-modal reasoning (CMR), the process of understanding and reasoning across different modalities, has emerged as a pivotal area with applications spanning from multimedia analysis to healthcare diagnostics. As the…
Multispectral pedestrian detection is a crucial component in various critical applications. However, a significant challenge arises due to the misalignment between these modalities, particularly under real-world conditions where data often…
What does it truly mean for a language model to "reason"? Current evaluations reward models' correct standalone answers-but correctness alone reveals little about the process that produced them. We argue that reasoning should be understood…
This volume contains the proceedings of EXPRESS/SOS 2025: the Combined 32nd International Workshop on Expressiveness in Concurrency and the 22nd Workshop on Structural Operational Semantics, which was held in Aarhus, Denmark, as an…
Time domain astronomy has come of age with astronomers now able to monitor the sky at high cadence both across the electromagnetic spectrum and using neutrinos and gravitational waves. The advent of new observing facilities permits new…
Aspect-level sentiment analysis aims to determine the sentiment polarity towards a specific target in a sentence. The main challenge of this task is to effectively model the relation between targets and sentiments so as to filter out noisy…
3D spatial reasoning in dynamic, audio-visual environments is a cornerstone of human cognition yet remains largely unexplored by existing Audio-Visual Large Language Models (AV-LLMs) and benchmarks, which predominantly focus on static or 2D…
Nowadays computer science can create digital worlds that deeply immerse users; it can also process in real time brain activity to infer their inner states. What marvels can we achieve with such technologies? Go back to displaying text. And…
We present a framework for perspective-aware reasoning in vision-language models (VLMs) through mental imagery simulation. Perspective-taking, the ability to perceive an environment or situation from an alternative viewpoint, is a key…
Vision-and-language navigation (VLN) is a crucial but challenging cross-modal navigation task. One powerful technique to enhance the generalization performance in VLN is the use of an independent speaker model to provide pseudo instructions…
Summmary talk at the Workshop on Sin and Flavour in Hadronic and Electromagnetic Interactions, Turin (Italy), september 1992, to appear in the Proceedings,
Innovations in interaction design are increasingly driven by progress in machine learning fields. Automatic speech emotion recognition (SER) is such an example field on the rise, creating well performing models, which typically take as…
Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human evaluation datasets for text simplification have limited…
Concentration is significant for maximizing potential in any activity. However, traditional methods to improve it often lack direct and natural feedback. We propose an innovative and inspiring VR system to experience and improve…
Earth vision has achieved milestones in geospatial object recognition but lacks exploration in object-relational reasoning, limiting comprehensive scene understanding. To address this, a progressive Earth vision-language understanding and…