PPaperPicks

Pradeep Varakantham

21 papers at tracked venues · 15 at CORE A* · active 2024–2026

DBLP profile ↗ORCID 0000-0001-7342-5745 ↗

Venues

AAAI ×7AAMAS ×4ICLR ×4NeurIPS ×4ECAI ×1NAACL ×1

Frequent coauthors

Huy Hoang
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Jayden Teoh Jing Teoh
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Hao Jiang
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Roman Belaire
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Yuxiao Lu
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Wenjun Li
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Shashank Reddy Chirra
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Changyu Chen
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Sidney Tio
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Dexun Li
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Ze Gong
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Zichang Ge
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Papers

  1. Optimizing Ride-Pooling Operations with Extended Pickup and Drop-Off Flexibility
    AAAI 2026 ·
    Hao Jiang
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  2. Bootstrapping Language Models with DPO Implicit Rewards
    ICLR 2025 ·
    Changyu Chen
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  3. EduQate: Generating Adaptive Curricula through RMABs in Education Settings
    AAMAS 2025 ·
    Sidney Tio
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  4. Marginal Benefit Driven RL Teacher for Unsupervised Environment Design
    AAAI 2025 ·
    Dexun Li
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  5. No Experts, No Problem: Avoidance Learning from Bad Demonstrations
    NeurIPS 2025 ·
    Huy Hoang
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  6. Offline Safe Reinforcement Learning Using Trajectory Classification
    AAAI 2025 ·
    Ze Gong
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  7. On Generalization Across Environments In Multi-Objective Reinforcement Learning
    ICLR 2025 ·
    Jayden Teoh
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  8. On Learning Informative Trajectory Embeddings for Imitation, Classification and Regression
    AAMAS 2025 ·
    Zichang Ge
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  9. On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
    ICLR 2025 ·
    Roman Belaire
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  10. Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
    ICLR 2025 ·
    Yuxiao Lu
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  11. Unlocking the Planning Capabilities of Large Language Models with Maximum Diversity Fine-tuning
    NAACL 2025 ·
    Wenjun Li
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  12. Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning
    AAAI 2024 ·
    Yuxiao Lu
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  13. Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning
    AAAI 2024 ·
    Huy Hoang
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  14. Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
    NeurIPS 2024 ·
    Jayden Teoh
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  15. Preserving the Privacy of Reward Functions in MDPs through Deception
    ECAI 2024 ·
    Shashank Reddy Chirra
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  16. Regret-based Defense in Adversarial Reinforcement Learning
    AAMAS 2024 ·
    Roman Belaire
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  17. Reward Penalties on Augmented States for Solving Richly Constrained RL Effectively
    AAAI 2024 ·
    Hao Jiang
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  18. SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning
    NeurIPS 2024 ·
    Huy Hoang
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  19. Safety through feedback in Constrained RL
    NeurIPS 2024 ·
    Shashank Reddy Chirra
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  20. Unifying Regret and State-Action Space Coverage for Effective Unsupervised Environment Design
    AAMAS 2024 ·
    Jayden Teoh Jing Teoh
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  21. Unsupervised Training Sequence Design: Efficient and Generalizable Agent Training
    AAAI 2024 ·
    Wenjun Li
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