Zhuo-Han Xie

Overview of the ImageCLEF 2026 Task on Multimodal Reasoning

SQLStructEval: Structural Evaluation of LLM Text-to-SQL Generation

SQLStructEval is introduced, a framework that analyzes this behavior through canonical abstract syntax tree representations and adopts a pipeline that first generates structured intermediate representations and then deterministically compiles them into SQL, improving execution accuracy and structural agreement among co...

Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document Understanding

Jev has the lowest cost and median response time among the evaluated configurations, while hosted language models achieve higher baseline accuracy and Rankings by baseline accuracy differ from rankings by correctness across every condition and repeat, although small differences in the latter do not establish a general...

Prediction-Market Seed Capital Recovery from Noise-Dominant Flow

Automated prediction markets require sponsors to prefund liquidity before observing order flow, creating a financing challenge at launch. We study whether nonnegative charges conditioned on observable payoff direction can improve recovery of this prefunded capital while limiting their effect on informed participation....

LLM-BabyBench: Can Language Models Plan in Worlds They Can Simulate?

Across seven frontier and open models, simulation is far ahead of planning for every model, near saturation for the strongest and well short of it for the weakest, and the length of the required solution, not grid size or obstacle count, governs planning failure.

FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?

This work introduces FinCUABuildBench, a benchmark for evaluating financial CUA task construction, and introduces FinCUABuildAgent, a multi-agent system for automatically constructing dynamic financial CUA evaluation tasks.

Jais 2: A Family of Arabic-Centric Open Large Language Models

Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong performance across the Arabic and culturally grounded benchmarks evaluated in this report. The family includes, to our knowledge, the largest...

Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close

When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer correctly within it. We call this setting normative pluralism and study it in Islamic finance using a four-choice taxonomy that separates framework selection from within-...

Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding

Think with Structured Grounding (TwSG), a novel fine-grained image perception framework designed to internalize complex images's tool-use capabilities within the model, is proposed, endowing models with native fine-grained region description and flexible reasoning capabilities.

FinExam-10K: When Retrieval Helps Financial Reasoning?

Professional financial examinations require models to combine domain knowledge, calculation, and judgment, yet no benchmark covers the full CFA and FRM structure under one protocol. We introduce FinExam-10K, to our knowledge the largest reported English benchmark for this setting, with 10,198 expert-reannotated questio...

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

FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence over multilingual evidence using document retrieval-augmented generation, cross-lingual evidence handling, structured prompting, answer compression, and validation strategies.

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

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 correct answer to finance questions involving domain terminology, numerical interpretation, and conceptual financial reasoning across languages...