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Sarath Sreedharan

28 papers · 2017–2026 · 5 venues · across top CS/AI venues

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+11 more ↓ πŸ—ΊοΈ Taxonomy Completionist (28) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Sprint πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
πŸ† Grand Slam 🀝 Dynamic Duo (17) πŸ† Keyword Champion (3) πŸ”¬ Deep Specialist (14) 🌈 Renaissance Researcher (6) πŸ”₯ Unstoppable Β· Silver ❓ The Questioner (2) ⚑ Prolific Year Β· Productive πŸ’Ž Century Club Β· Bronze πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (119)

Papers

Explanations for Sequential Decision-Making – an Overview AAAI 2026 Inferring Implicit Goals Across Differing Task Models AAAI 2026 Mental Model-based Generation of Lies for Insider Threat Modeling AAAI 2026 Reducing Goal State Divergence with Environment Design AAAI 2026 A Survey on Model Repair in AI Planning IJCAI 2025 Explain It as Simple as Possible, but No Simpler – Explanation via Model Simplification for Addressing Inferential Gap (Abstract Reprint) IJCAI 2025 A Wireframe-Based Approach for Classifying and Acquiring Proficiency in the American Sign Language (Student Abstract) AAAI 2024 Can LLMs Fix Issues with Reasoning Models? Towards More Likely Models for AI Planning AAAI 2024 Expectation Alignment: Handling Reward Misspecification in the Presence of Expectation Mismatch NeurIPS 2024 Goal Alignment: Re-analyzing Value Alignment Problems Using Human-Aware AI AAAI 2024 Human-Aware AI – A Foundational Framework for Human-AI Interaction AAAI 2023 Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning NeurIPS 2023 On the Planning Abilities of Large Language Models - A Critical Investigation NeurIPS 2023 Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates NeurIPS 2023 PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change NeurIPS 2023 Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations ICLR 2022 Leveraging Approximate Symbolic Models for Reinforcement Learning via Skill Diversity ICML 2022 On the Computational Complexity of Model Reconciliations IJCAI 2022 Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems AAAI 2022 A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI Interaction IJCAI 2021 RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions AAAI 2021 Expectation-Aware Planning: A Unifying Framework for Synthesizing and Executing Self-Explaining Plans for Human-Aware Planning AAAI 2020 The Emerging Landscape of Explainable Automated Planning & Decision Making IJCAI 2020 Balancing Explicability and Explanations in Human-Aware Planning IJCAI 2019 Model-Free Model Reconciliation IJCAI 2019 Why Can’t You Do That HAL? Explaining Unsolvability of Planning Tasks IJCAI 2019 Hierarchical Expertise Level Modeling for User Specific Contrastive Explanations IJCAI 2018 Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy IJCAI 2017