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20242026
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cs.AI2026

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer

Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana

Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learning (RL) agents typically require…

cs.AI2026

Shared Latent Structures Enable Unified Backdoor Detection and Mitigation in LLMs

Omar Mahmoud, Aly M. Kassem, Thommen George Karimpanal +4

Backdoor attacks in large language models (LLMs) are often treated as isolated trigger-response failures, motivating defenses tailored to specific triggers or behaviors. We show th…

cs.AI2026

ASPECT:Analogical Semantic Policy Execution via Language Conditioned Transfer

Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana

Reinforcement Learning (RL) agents often struggle to generalize knowledge to new tasks, even those structurally similar to ones they have mastered. Although recent approaches have…

cs.AI2025

Dynamic Policy Fusion for User Alignment Without Re-Interaction

Ajsal Shereef Palattuparambil, Thommen George Karimpanal, Santu Rana

Deep reinforcement learning (RL) policies, although optimal in terms of task rewards, may not align with the personal preferences of human users. To ensure this alignment, a naive…

cs.AI2025

Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer

Minh Hoang Nguyen, Linh Le Pham Van, Thommen George Karimpanal +2

Decision Transformers (DT) play a crucial role in modern reinforcement learning, leveraging offline datasets to achieve impressive results across various domains. However, DT requi…