7 papers
Evaluating the Diagnostic Robustness of Vision-Language Models Under Visual and Textual Perturbations
Ali Khoramfar, Mohammad Javad Dousti, Alireza Mohamadian +1
Standard accuracy metrics for VLMs often mask significant reliability failures in sensitive domains. In this work, we utilize a histopathology-validated brain MRI dataset to system…
MDP-GRPO: Stabilized Group Relative Policy Optimization for Multi-Constraint Instruction Following
Mohammad Mahdi Salmani-Zarchi, Zahra Rahimi, Heshaam Faili +1
Reinforcement learning with verifiable rewards is ideal for multi-constraint instruction following, yet standard group-relative policy optimization (GRPO) becomes unstable under di…
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…
Dynamic Jointly Batch Selection for Data Efficient Machine Translation Fine-Tuning
Mohammad Amin Ghanizadeh, Mohammad Javad Dousti
Data quality and its effective selection are fundamental to improving the performance of machine translation models, serving as cornerstones for achieving robust and reliable trans…
: Data-Driven LoRA Initialization for Low Resource Tasks
Javad SeraJ, Mohammad Mahdi Mohajeri, Mohammad Javad Dousti
Tuning large language models is essential for optimizing their performance across diverse applications, particularly in scenarios with limited data availability. Tuning large langu…
Towards Data-Efficient Language Models: A Child-Inspired Approach to Language Learning
Mohammad Amin Ghanizadeh, Mohammad Javad Dousti
In this work, we explain our approach employed in the BabyLM Challenge, which uses various methods of training language models (LMs) with significantly less data compared to tradit…