7 citations · 10 across the 11 of their papers we have counts for
14 papers
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…
StretchBot: A Neuro-Symbolic Framework for Adaptive Guidance with Assistive Robots
Luca Vogelgesang, Ahmed Mehdi Soltani, Mohammadhossein Khojasteh +4
Assistive robots have growing potential to support physical wellbeing in home and healthcare settings, for example, by guiding users through stretching or rehabilitation routines.…
Enhancing Structural Mapping with LLM-derived Abstractions for Analogical Reasoning in Narratives
Mohammadhossein Khojasteh, Yifan Jiang, Stefano De Giorgis +2
Analogical reasoning is a key driver of human generalization in problem-solving and argumentation. Yet, analogies between narrative structures remain challenging for machines. Cogn…
The Carbon Footprint Wizard: A Knowledge-Augmented AI Interface for Streamlining Food Carbon Footprint Analysis
Mustafa Kaan Aslan, Reinout Heijungs, Filip Ilievski
Environmental sustainability, particularly in relation to climate change, is a key concern for consumers, producers, and policymakers. The carbon footprint, based on greenhouse gas…
A Study of Commonsense Reasoning over Visual Object Properties
Abhishek Kolari, Mohammadhossein Khojasteh, Yifan Jiang +2
Inspired by human categorization, visual reasoning about object properties, such as physical attributes and functions, involves identifying and recognizing low-level details and hi…
Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations
Bradley P. Allen, Prateek Chhikara, Thomas Macaulay Ferguson +2
Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but exhibit problems with logical consistency in their outp…
Clustering Internet Memes Through Template Matching and Multi-Dimensional Similarity
Tygo Bloem, Filip Ilievski
Meme clustering is critical for toxicity detection, virality modeling, and typing, but it has received little attention in previous research. Clustering similar Internet memes is c…
Investigating the Robustness of Deductive Reasoning with Large Language Models
Fabian Hoppe, Filip Ilievski, Jan-Christoph Kalo
Large Language Models (LLMs) have been shown to achieve impressive results for many reasoning-based NLP tasks, suggesting a degree of deductive reasoning capability. However, it re…
Commonsense Video Question Answering through Video-Grounded Entailment Tree Reasoning
Huabin Liu, Filip Ilievski, Cees G. M. Snoek
This paper proposes the first video-grounded entailment tree reasoning method for commonsense video question answering (VQA). Despite the remarkable progress of large visual-langua…
Aligning Generalisation Between Humans and Machines
Filip Ilievski, Barbara Hammer, Frank van Harmelen +22
Recent advances in AI -- including generative approaches -- have resulted in technology that can support humans in scientific discovery and forming decisions, but may also disrupt…
Standardizing Knowledge Engineering Practices with a Reference Architecture
Bradley P. Allen, Filip Ilievski
Knowledge engineering is the process of creating and maintaining knowledge-producing systems. Throughout the history of computer science and AI, knowledge engineering workflows hav…
Knowledge-Powered Recommendation for an Improved Diet Water Footprint
Saurav Joshi, Filip Ilievski, Jay Pujara
According to WWF, 1.1 billion people lack access to water, and 2.7 billion experience water scarcity at least one month a year. By 2025, two-thirds of the world's population may be…
Contextualizing Internet Memes Across Social Media Platforms
Saurav Joshi, Filip Ilievski, Luca Luceri
Internet memes have emerged as a novel format for communication and expressing ideas on the web. Their fluidity and creative nature are reflected in their widespread use, often acr…
Contextualized Scene Imagination for Generative Commonsense Reasoning
PeiFeng Wang, Jonathan Zamora, Junfeng Liu +3
Humans use natural language to compose common concepts from their environment into plausible, day-to-day scene descriptions. However, such generative commonsense reasoning (GCSR) s…