1 citations · 1 across the 6 of their papers we have counts for
6 papers
Steering Geometry: Validating Human Value Geometry in LLM Steering Space
Mohammad Mahdi Abootorabi, Armin Saghafian, Ali Bazshoushtari +5
As large language models (LLMs) are increasingly deployed in alignment-sensitive contexts, activation steering has emerged as a lightweight, inference-time alternative to fine-tuni…
The Hidden Bias of Process Reward Models:PRISM for Rewarding the Right Reasoning
Aakriti Agrawal, Souradip Chakraborty, Armin Saghafian +6
Process Reward Models (PRMs) improve credit assignment for reasoning by providing step-level feedback. However, we identify a hidden bias in PRMs caused by severe imbalance in step…
T2I-FineEval: Fine-Grained Compositional Metric for Text-to-Image Evaluation
Seyed Mohammad Hadi Hosseini, Amir Mohammad Izadi, Ali Abdollahi +2
Although recent text-to-image generative models have achieved impressive performance, they still often struggle with capturing the compositional complexities of prompts including a…
Fine-Grained Alignment and Noise Refinement for Compositional Text-to-Image Generation
Amir Mohammad Izadi, Seyed Mohammad Hadi Hosseini, Soroush Vafaie Tabar +3
Text-to-image generative models have made significant advancements in recent years; however, accurately capturing intricate details in textual prompts-such as entity missing, attri…
CAREL: Instruction-guided reinforcement learning with cross-modal auxiliary objectives
Armin Saghafian, Amirmohammad Izadi, Negin Hashemi Dijujin +1
Grounding the instruction in the environment is a key step in solving language-guided goal-reaching reinforcement learning problems. In automated reinforcement learning, a key conc…
ComAlign: Compositional Alignment in Vision-Language Models
Ali Abdollah, Amirmohammad Izadi, Armin Saghafian +5
Vision-language models (VLMs) like CLIP have showcased a remarkable ability to extract transferable features for downstream tasks. Nonetheless, the training process of these models…