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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.
Neuron steering reinforces dialect in some varieties when the prompt is already dialectal but cannot induce it from MSA prompts, whereas vector steering succeeds in both settings, and Arabic dialects are therefore steerable mainly through distributed rather than localized representations.
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...
A semantic correctness taxonomy is introduced that assigns open-ended answers to eight ordered classes, separating verbose-but-correct answers from those contaminated by hallucinated content and CAP (Context-Aware Precision), a reference-based metric that scores question-conditioned statements using bidirectional NLI.
This work introduces EDRAC, the first large-scale benchmark for dialectal Arabic machine reading comprehension (MRC) and generative QA, covering five major dialects: Egyptian, Moroccan, Emirati, Syrian, and Saudi Arabic, and benchmarks Arabic-centric and multilingual LLMs on EDRAC using lexical and semantic metrics.
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-...
MIRAGE, a training-free, model-agnostic defense for long-form RAG, is introduced, a training-free, model-agnostic defense for long-form RAG that consistently restores factuality under mixed and fully polluted evidence and outperforms prior robust-RAG methods.
TradeLens is introduced, a trace-grounded diagnostic toolkit for evaluating agentic trading systems from their trading records, runtime traces, and deployment configurations, which reframe the evaluation of LLM-based trading agents from capability-centric performance ranking to trace-grounded diagnosis of intelligence-...
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.
SurakshaEval is introduced, a novel safety benchmark composed of human-written prompts spanning real-world scenarios, explicitly designed for ten major Indian languages - Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, and Telugu - along with English.
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.
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...
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