10 papers
On-Policy Distillation of Language Models for Autonomous Vehicle Motion Planning
Amirhossein Afsharrad, Amirhesam Abedsoltan, Ahmadreza Moradipari +1
Large language models (LLMs) have recently demonstrated strong potential for autonomous vehicle motion planning by reformulating trajectory prediction as a language generation prob…
Beyond Binary Preferences: A Principled Framework for Reward Modeling with Ordinal Feedback
Amirhossein Afsharrad, Ruida Zhou, Luca Viano +2
Reward modeling is crucial for aligning large language models with human preferences, yet current approaches lack a principled mathematical framework for leveraging ordinal prefere…
The Gray Area: Characterizing Moderator Disagreement on Reddit
Shayan Alipour, Shruti Phadke, Seyed Shahabeddin Mousavi +3
Volunteer moderators play a crucial role in sustaining online dialogue, but they often disagree about what should or should not be allowed. In this paper, we study the complexity o…
Evaluating Speech-to-Text x LLM x Text-to-Speech Combinations for AI Interview Systems
Rumi Allbert, Nima Yazdani, Ali Ansari +3
Voice-based conversational AI systems increasingly rely on cascaded architectures that combine speech-to-text (STT), large language models (LLMs), and text-to-speech (TTS) componen…
LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
Borna Khodabandeh, Amirabbas Afzali, Amirhossein Afsharrad +4
Visual encoders have become fundamental components in modern computer vision pipelines. However, ensuring robustness against adversarial perturbations remains a critical challenge.…
One Goal, Many Challenges: Robust Preference Optimization Amid Content-Aware and Multi-Source Noise
Amirabbas Afzali, Amirhossein Afsharrad, Seyed Shahabeddin Mousavi +1
Large Language Models (LLMs) have made significant strides in generating human-like responses, largely due to preference alignment techniques. However, these methods often assume u…
Cooperative Multi-Agent Constrained Stochastic Linear Bandits
Amirhossein Afsharrad, Parisa Oftadeh, Ahmadreza Moradipari +1
In this study, we explore a collaborative multi-agent stochastic linear bandit setting involving a network of agents that communicate locally to minimize their collective regre…
Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers
Davide Celestini, Amirhossein Afsharrad, Daniele Gammelli +6
Effective trajectory generation is essential for reliable on-board spacecraft autonomy. Among other approaches, learning-based warm-starting represents an appealing paradigm for so…
Markov Decision Processes with Noisy State Observation
Amirhossein Afsharrad, Sanjay Lall
This paper addresses the challenge of a particular class of noisy state observations in Markov Decision Processes (MDPs), a common issue in various real-world applications. We focu…
Convex Methods for Constrained Linear Bandits
Amirhossein Afsharrad, Ahmadreza Moradipari, Sanjay Lall
Recently, bandit optimization has received significant attention in real-world safety-critical systems that involve repeated interactions with humans. While there exist various alg…