papers

Publications (13)

cs.AI2026

The Geometry of Forgetting: Temporal Knowledge Drift as an Independent Axis in LLM Representations

Rania Elbadry, Ahmed Heakl, Fan Zhang +4

Large language models confidently produce outdated answers, and no existing method can detect them. We show this is not an engineering failure but a structural one: temporal drift,…

cs.CL2026

Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering

Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18

FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question with financial statements and n…

cs.LG2026

CEPO: RLVR Self-Distillation using Contrastive Evidence Policy Optimization

Ahmed Heakl, Abdelrahman M. Shaker, Youssef Mohamed +4

When a model produces a correct solution under reinforcement learning with verifiable rewards (RLVR), every token receives the same reward signal regardless of whether it was a dec…

cs.CL2026

Instruction-Guided Poetry Generation in Arabic and Its Dialects

Abdelrahman Sadallah, Kareem Elozeiri, Mervat Abassy +5

Poetry has long been a central art form for Arabic speakers, serving as a powerful medium of expression and cultural identity. While modern Arabic speakers continue to value poetry…

cs.CL2026

The CLEF-2026 FinMMEval Lab: Multilingual and Multimodal Evaluation of Financial AI Systems

Zhuohan Xie, Rania Elbadry, Fan Zhang +12

We present the setup and the tasks of the FinMMEval Lab at CLEF 2026, which introduces the first multilingual and multimodal evaluation framework for financial Large Language Model…

cs.CL2026

FinPersona-Bench: A Benchmark for Longitudinal Psychometric Stability of Autonomous Financial Agents

Muhammad Usman Safder, Ayesha Gull, Rania Elbadry +7

Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as "preserve capital" or "avoid speculative…

cs.CL2026

SAHM: A Benchmark for Arabic Financial and Shari'ah-Compliant Reasoning

Rania Elbadry, Sarfraz Ahmad, Ahmed Heakl +12

English financial NLP has advanced rapidly through benchmarks targeting earnings analysis, market sentiment, tabular reasoning, and financial question answering, yet Arabic financi…

cs.CL2026

Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering

Zhuohan Xie, Yuyang Dai, Rania Elbadry +18

FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests whether systems can select the corr…

cs.CL2026

FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning

Zhuohan Xie, Daniil Orel, Rushil Thareja +22

Multi-step symbolic reasoning is essential for robust financial analysis; yet, current benchmarks largely overlook this capability. Existing datasets such as FinQA and ConvFinQA em…

cs.CL2026

FinReporting: An Agentic Workflow for Localized Reporting of Cross-Jurisdiction Financial Disclosures

Fan Zhang, Mingzi Song, Rania Elbadry +20

Financial reporting systems increasingly leverage Large Language Models (LLMs) to extract and summarize corporate disclosures. However, most existing approaches assume a single-mar…

cs.CL2026

DocAtlas: Multilingual Document Understanding Across 80+ Languages

Ahmed Heakl, Youssef Mohamed, Abdullah Sohail +6

Multilingual document understanding remains limited for low-resource languages due to scarce training data and model-based annotation pipelines that perpetuate existing biases. We…

cs.CL2026

EngTrace: A Symbolic Benchmark for Verifiable Process Supervision of Engineering Reasoning

Ayesha Gull, Muhammad Usman Safder, Rania Elbadry +4

Large Language Models (LLMs) are increasingly entering specialized, safety-critical engineering workflows governed by strict quantitative standards and immutable physical laws, mak…

cs.AI2026

Herculean: An Agentic Benchmark for Financial Intelligence

Xueqing Peng, Zhuohan Xie, Yupeng Cao +60

As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carry out financial professional…