21 citations · 45 across the 12 of their papers we have counts for
13 papers
Tasks over Application Manuals: Revealing Gaps in Long-Horizon Procedural Reasoning for Language Models
Utkarsh Soni, Syed Shariyar Murtaza, Yifan Nie +2
Large language models (LLMs) have achieved strong performance on a wide range of natural language tasks, and recent benchmarks suggest that they are increasingly adept at multi-hop…
When Synthetic Data Hurts: On Catastrophic Forgetting in Skill Retrieval for LLM Agents
Syed Shariyar Murtaza, Yifan Nie, Utkarsh Soni +2
LLM agents increasingly rely on external skills retrieved at runtime, making skill selection from large repositories a critical challenge. We present a production skill router over…
Control-Data Flow Separation: Stable Prompt Optimization in Multi-Agent LLMs
Wentao Zhang, Syed Shariyar Murtaza, Junaid Ahmad Bhatti +4
Prompt optimization can improve multi-agent LLM systems, but the prompts being optimized often serve two entangled roles: generating task-relevant content and specifying execution-…
PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models
Aditi Mishra, Utkarsh Soni, Anjana Arunkumar +3
Large Language Models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language prompt.…
Methods and Mechanisms for Interactive Novelty Handling in Adversarial Environments
Tung Thai, Ming Shen, Mayank Garg +10
Learning to detect, characterize and accommodate novelties is a challenge that agents operating in open-world domains need to address to be able to guarantee satisfactory task perf…
Towards customizable reinforcement learning agents: Enabling preference specification through online vocabulary expansion
Utkarsh Soni, Nupur Thakur, Sarath Sreedharan +4
There is a growing interest in developing automated agents that can work alongside humans. In addition to completing the assigned task, such an agent will undoubtedly be expected t…
Integrating Planning, Execution and Monitoring in the presence of Open World Novelties: Case Study of an Open World Monopoly Solver
Sriram Gopalakrishnan, Utkarsh Soni, Tung Thai +3
The game of monopoly is an adversarial multi-agent domain where there is no fixed goal other than to be the last player solvent, There are useful subgoals like monopolizing sets of…
Not all users are the same: Providing personalized explanations for sequential decision making problems
Utkarsh Soni, Sarath Sreedharan, Subbarao Kambhampati
There is a growing interest in designing autonomous agents that can work alongside humans. Such agents will undoubtedly be expected to explain their behavior and decisions. While g…
Why? Why not? When? Visual Explanations of Agent Behavior in Reinforcement Learning
Aditi Mishra, Utkarsh Soni, Jinbin Huang +1
Reinforcement learning (RL) is used in many domains, including autonomous driving, robotics, stock trading, and video games. Unfortunately, the black box nature of RL agents, combi…
Let Me At Least Learn What You Really Like: Dealing With Noisy Humans When Learning Preferences
Sriram Gopalakrishnan, Utkarsh Soni
Learning the preferences of a human improves the quality of the interaction with the human. The number of queries available to learn preferences maybe limited especially when inter…
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations
Sarath Sreedharan, Utkarsh Soni, Mudit Verma +2
As increasingly complex AI systems are introduced into our daily lives, it becomes important for such systems to be capable of explaining the rationale for their decisions and allo…
Same Stats, Different Graphs: Exploring the Space of Graphs in Terms of Graph Properties
Hang Chen, Vahan Huroyan, Utkarsh Soni +3
Data analysts commonly utilize statistics to summarize large datasets. While it is often sufficient to explore only the summary statistics of a dataset (e.g., min/mean/max), Anscom…
Same Stats, Different Graphs (Graph Statistics and Why We Need Graph Drawings)
Hang Chen, Utkarsh Soni, Yafeng Lu +3
Data analysts commonly utilize statistics to summarize large datasets. While it is often sufficient to explore only the summary statistics of a dataset (e.g., min/mean/max), Anscom…