9 citations · 9 across the 4 of their papers we have counts for
6 papers
Multi-Head Latent Control: A Unified Interface for LLM Agent Decision Making
Amirhosein Ghasemabadi, Ruichen Chen, Bahador Rashidi +1
Large language models are increasingly deployed as agents, but reliable agentic behavior requires more than next-token prediction. At inference time, it is preferred that an agent…
Can LLMs Predict Their Own Failures? Self-Awareness via Internal Circuits
Amirhosein Ghasemabadi, Di Niu
Large language models (LLMs) generate fluent and complex outputs but often fail to recognize their own mistakes and hallucinations. Existing approaches typically rely on external j…
Grounding Degradations in Natural Language for All-In-One Video Restoration
Muhammad Kamran Janjua, Amirhosein Ghasemabadi, Kunlin Zhang +3
In this work, we propose an all-in-one video restoration framework that grounds degradation-aware semantic context of video frames in natural language via foundation models, offeri…
Guided by Gut: Efficient Test-Time Scaling with Reinforced Intrinsic Confidence
Amirhosein Ghasemabadi, Keith G. Mills, Baochun Li +1
Test-Time Scaling (TTS) methods for enhancing Large Language Model (LLM) reasoning often incur substantial computational costs, primarily due to extensive reliance on external Proc…
Learning Truncated Causal History Model for Video Restoration
Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh +1
One key challenge to video restoration is to model the transition dynamics of video frames governed by motion. In this work, we propose TURTLE to learn the truncated causal history…
CascadedGaze: Efficiency in Global Context Extraction for Image Restoration
Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh +3
Image restoration tasks traditionally rely on convolutional neural networks. However, given the local nature of the convolutional operator, they struggle to capture global informat…