arXiv AI July 29, 2026 By Sagnik Sinha, Shreyas Shrestha

DS@GT ARC at CheckThat! 2026: LLM-Based Trace Ranking and Grouped Reward Modeling for Multilingual Numerical Claim Verification

arXiv:2607. 25069v1 Announce Type: cross Abstract: Automated verification of numerical claims is a challenging problem, as it requires both language understanding and quantitative reasoning.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Computation and Language

Sep 22

What Makes Good Multilingual Reasoning? Disentangling Traces with Measurable Features

arXiv:2604.04720v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) still exhibit large performance gaps between English and other languages, yet much current work assumes these gaps ca...

By Dayeon Ki, Kevin Duh, Marine Carpuat

benchmarks safety

arXiv AI

Jun 9

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

arXiv:2606. 09380v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a leading paradigm for improving the reasoning ability of large language models through outcome-based supervision.

By Han Zhou, Adam X. Yang, Laurence Aitchison, Anna Korhonen, Albert Q. Jiang

llms reinforcement-learning benchmarks

arXiv AI

Sep 10

UniRRM: Unified Reasoning Reward Models Across Languages and Evaluation Paradigms

arXiv:2609.05910v1 Announce Type: cross Abstract: Reinforcement learning (RL) excels on tasks with verifiable rewards, but in open-ended tasks, the reliability of reward models remains a key challeng...

By Peng Lai, Yichao Du, Junchao Wu, Weibo Gao, Linan Yue, Longyue Wang, Weihua Luo, Derek F. Wong, Guanhua Chen

llms reinforcement-learning benchmarks safety

arXiv Computation and Language

Sep 23

ARAFA: An LLM-Generated Arabic Fact-Checking Dataset

A new large-scale Arabic fact‑checking dataset called Arafa has been created using an automated pipeline that generates claims from Arabic Wikipedia, mutates them into counterfactuals, and validates them against supporting or refuting evidence. The dataset contains 181,976 claim‑evidence pairs labeled as supported, refuted, or not enough information, and human evaluation shows high inter‑annotator agreement and strong validation accuracy. Fine‑tuned transformer models on Arafa achieve a Macro F1‑score of 77%, demonstrating its usefulness for Arabic fact‑checking tasks.

By Christophe Khalil, Shady Elbassuoni, Rida Assaf

llms nlp fine-tuning

arXiv AI

Jul 28

Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval

arXiv:2607. 22841v1 Announce Type: cross Abstract: We present DS@GT's submission to FinMMEval 2026 Task 1, a multilingual financial exam question answering benchmark spanning English, Spanish, Greek, Chinese, and Hindi.

By Justice Ayela, Kabir Sahni

llms rag nlp benchmarks

arXiv Machine Learning

Aug 12

Reinforcement Learning-based Semi-supervised Knowledge Distillation with LLM-as-a-Judge

arXiv:2604. 02621v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) substantially improves the reasoning capabilities of language models, but most existing RL fine-tuning approaches rely entirely on ground-truth verifiable rewards and thus labeled datasets with verifiable answers.

By Yiyang Shen, Lifu Tu, Weiran Wang

llms reinforcement-learning fine-tuning efficiency

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Related stories

What Makes Good Multilingual Reasoning? Disentangling Traces with Measurable Features

Reasoning Arena: Trace Tournaments When Verifiable Rewards Fall Short

UniRRM: Unified Reasoning Reward Models Across Languages and Evaluation Paradigms

ARAFA: An LLM-Generated Arabic Fact-Checking Dataset

Language-Routed RAG and Direct Option Scoring for Multilingual Financial QA: DS@GT at FinMMEval

Reinforcement Learning-based Semi-supervised Knowledge Distillation with LLM-as-a-Judge