collaborators

13 papers

cs.CL2026

Rank Reversal in Multilingual LLM Judges: A Label-Free Double-Centering Calibrator

Alhasan Mahmood, Samir Abdaljalil, Hasan Kurban

Multilingual LLM judges produce different evaluator-backbone rankings depending on the prompt language: on an eight-language Agent-as-a-Judge benchmark, the top-ranked backbone alt…

cs.CV2026

ConfTriage: A Calibration-Aware LLM Triage Framework for Pulmonary Nodule Malignancy with Selective Specialist Deferral

Md Rabiul Islam, Samir Abdaljalil, Erchin Serpedin +1

Pulmonary nodule malignancy prediction typically depends on image-trained specialist deep learning (DL) models that require substantial annotated imaging data and task-specific tra…

cs.CL2026

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation

Alhasan Mahmood, Samir Abdaljalil, Hasan Kurban

Evaluation language is typically treated as a fixed English default in agentic code benchmarks, yet we show that changing the judge's language can invert backbone rankings. We loca…

cs.CL2026

IsoSci: A Benchmark of Isomorphic Cross-Domain Science Problems for Evaluating Reasoning versus Knowledge Retrieval in LLMs

Samir Abdaljalil, Erchin Serpedin, Hasan Kurban

We introduce ISOSCI, a benchmark of isomorphic cross-domain science problem pairs that separates reasoning ability from domain knowledge retrieval in LLM evaluation. Each pair shar…

cs.CV2026

4D Synchronized Fields: Motion-Language Gaussian Splatting for Temporal Scene Understanding

Mohamed Rayan Barhdadi, Samir Abdaljalil, Rasul Khanbayov +2

Current 4D representations decouple geometry, motion, and semantics: reconstruction methods discard interpretable motion structure; language-grounded methods attach semantics after…

cs.CL2026

Knowing When Not to Answer: Abstention-Aware Scientific Reasoning

Samir Abdaljalil, Erchin Serpedin, Hasan Kurban

Large language models are increasingly used to answer and verify scientific claims, yet existing evaluations typically assume that a model must always produce a definitive answer.…