58 papers
FlowNeg: GFlowNet-Guided Diverse Hard Negative Sampling for Knowledge Graph Embedding
Ibne Farabi Shihab, Naoshin Anzum Hridi, Joyanta Jyoti Mondal
Negative sampling determines whether a knowledge graph embedding (KGE) model learns from informative counterexamples or wastes updates on implausible corruptions. Uniform negatives…
Calibration-Preserving Pruning: Compression as a Reliability Contract
Ibne Farabi Shihab, Adria Binte Habib, Anuj Sharma
Split conformal prediction, not the pruning rule, supplies finite-sample marginal coverage once a pruned model is fixed independently of the conformal calibration split. We study t…
The Cost of Adaptivity: Matching Lower Bounds Across Learning Problems
Ibne Farabi Shihab, Adria Binte Habib
Adaptive procedures must work without nuisance information an oracle may use, such as a gradient scale or smoothness index, and robust procedures may have to answer queries whose c…
Stateful CARS: Exact Cross-History Reuse for Policy-Constrained LLM Agents
Ibne Farabi Shihab, Md Najmus Swaqeeb, Abu Sa-Adat Mohamed Moon-Im Al Ahsan
Tool-using language-model agents face constraints whose meaning changes with observations and prior actions. We study exact sampling from the model distribution conditioned on a ha…
Opportunity Is Not Realizability: Selection-Valid Diagnostics for Multi-LLM Routing
Ibne Farabi Shihab, Abu Sa-Adat Mohamed Moon-Im Al Ahsan, Md Najmus Swaqeeb
Oracle routing measures how much a pool of language models could gain from per-query selection, but the diagnostic has two flaws: testing against a best fixed model selected on the…
Quality-Diversity Stress Tests for Process Reward Models:What Archive Coverage Can and Cannot Certify
Ibne Farabi Shihab, Fariya Afrin
Process reward models (PRMs) score intermediate reasoning steps and are widely used for search, ranking, and training, but optimization can exploit these learned proxies by increas…