1 citations · 1 across the 27 of their papers we have counts for
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CODS: Iterative Bellman-Residual Data Selection for Reusable Offline Reinforcement Learning
Ibne Farabi Shihab, Sanjeda Akter, Abu Sa-Adat Mohamed Moon-Im Al Ahsan +2
Offline reinforcement learning repeatedly trains policies from a fixed transition pool, making redundant data costly across seeds and hyperparameters, while naive subsampling can r…
Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors
Ibne Farabi Shihab, Joyanta Jyoti Mondal, Anuj Sharma
Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guaranteed exposure inside a period…
Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces
Joyanta Jyoti Mondal, Ibne Farabi Shihab, Anuj Sharma
Contextual bandits with graph-structured arms arise in recommendation, citation retrieval, and social advertising, where arms connected on a graph tend to share reward signal. Stan…
EST-PRM: Stress-Testing Process Reward Models Before They Become Load-Bearing
Ibne Farabi Shihab, Fariya Afrin, Sanjeda Akter +1
Process reward models (PRMs) are widely used in language-model training with dense step-level supervision. They assume PRM scores are stable proxies for step correctness under labe…
Grounded Decoding: Retrieval-Anchored Probability Fusion for Faithful RAG
Ibne Farabi Shihab, Fariya Afrin, Sanjeda Akter +1
As retrieval-augmented generation (RAG) systems scale, it becomes increasingly challenging to ensure faithful grounding in external evidence. Large language models may still priori…
Topology-Aware State Abstraction with Tangle Cores for Markov Decision Processes
Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma
State abstraction in reinforcement learning is usually formulated as a partition of states based on reward and transition similarity. This excludes a common structural pattern in n…