59 citations · 64 across the 12 of their papers we have counts for
13 papers
Exploiting Expertise of Non-Expert and Diverse Agents in Social Bandit Learning: A Free Energy Approach
Erfan Mirzaei, Seyed Pooya Shariatpanahi, Alireza Tavakoli +2
Personalized AI-based services involve a population of individual reinforcement learning agents. However, most reinforcement learning algorithms focus on harnessing individual lear…
A Dual-Axis Taxonomy of Knowledge Editing for LLMs: From Mechanisms to Functions
Amir Mohammad Salehoof, Ali Ramezani, Yadollah Yaghoobzadeh +1
Large language models (LLMs) acquire vast knowledge from large text corpora, but this information can become outdated or inaccurate. Since retraining is computationally expensive,…
DeepQuestion: Systematic Generation of Real-World Challenges for Evaluating LLMs Performance
Ali Khoramfar, Ali Ramezani, Mohammad Mahdi Mohajeri +3
While Large Language Models (LLMs) achieve near-human performance on standard benchmarks, their capabilities often fail to generalize to complex, real-world problems. To bridge thi…
Optimizing Alignment with Less: Leveraging Data Augmentation for Personalized Evaluation
Javad Seraj, Mohammad Mahdi Mohajeri, Mohammad Javad Dousti +1
Automatic evaluation by large language models (LLMs) is a prominent topic today; however, judgment and evaluation tasks are often subjective and influenced by various factors, maki…
Subgoal Discovery Using a Free Energy Paradigm and State Aggregations
Amirhossein Mesbah, Reshad Hosseini, Seyed Pooya Shariatpanahi +1
Reinforcement learning (RL) plays a major role in solving complex sequential decision-making tasks. Hierarchical and goal-conditioned RL are promising methods for dealing with two…
AI-powered Digital Framework for Personalized Economical Quality Learning at Scale
Mrzieh VatandoustMohammadieh, Mohammad Mahdi Mohajeri, Ali Keramati +1
The disparity in access to quality education is significant, both between developed and developing countries and within nations, regardless of their economic status. Socioeconomic…
A Survey On Enhancing Reinforcement Learning in Complex Environments: Insights from Human and LLM Feedback
Alireza Rashidi Laleh, Majid Nili Ahmadabadi
Reinforcement learning (RL) is one of the active fields in machine learning, demonstrating remarkable potential in tackling real-world challenges. Despite its promising prospects,…
CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt
Mohammad Mahdi Mohajeri, Mohammad Javad Dousti, Majid Nili Ahmadabadi
Text classification is a fundamental task in natural language processing (NLP), and large language models (LLMs) have demonstrated their capability to perform this task across vari…
Risk Sensitivity in Markov Games and Multi-Agent Reinforcement Learning: A Systematic Review
Hafez Ghaemi, Shirin Jamshidi, Mohammad Mashreghi +2
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been r…
Reinforcement Learning with Subspaces using Free Energy Paradigm
Milad Ghorbani, Reshad Hosseini, Seyed Pooya Shariatpanahi +1
In large-scale problems, standard reinforcement learning algorithms suffer from slow learning speed. In this paper, we follow the framework of using subspaces to tackle this proble…
Multi-Representational Learning for Offline Signature Verification using Multi-Loss Snapshot Ensemble of CNNs
Saeed Masoudnia, Omid Mersa, Babak N. Araabi +3
Offline Signature Verification (OSV) is a challenging pattern recognition task, especially in presence of skilled forgeries that are not available during training. This study aims…
Exploiting generalization in the subspaces for faster model-based learning
Maryam Hashemzadeh, Reshad Hosseini, Majid Nili Ahmadabadi
Due to the lack of enough generalization in the state-space, common methods in Reinforcement Learning (RL) suffer from slow learning speed especially in the early learning trials.…
Incremental learning of high-level concepts by imitation
Mina Alibeigi, Majid Nili Ahmadabadi, Babak Nadjar Araabi
Nowadays, robots become a companion in everyday life. To be well-accepted by humans, robots should efficiently understand meanings of their partners' motions and body language, and…