activity
20242026
most citedOrion-14B: Open-source Multilingual Large Language Models

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

MARDoc: A Memory-Aware Refinement Agent Framework for Multimodal Long Document QA

Kaifeng Chen, Hongtao Liu, Qiyao Peng +4

Iterative retrieval-reasoning agents have recently shown promise for multimodal long-document question answering. However, most existing systems maintain a single growing context t…

cs.CL2026

Adam's Law: Textual Frequency Law on Large Language Models

Hongyuan Adam Lu, Z. L., Victor Wei +5

While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…

cs.CL2025

From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation

Seokhee Hong, Sunkyoung Kim, Guijin Son +3

The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…

cs.LG2025★ 1 cited

Assay2Mol: large language model-based drug design using BioAssay context

Yifan Deng, Spencer S. Ericksen, Anthony Gitter

Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…

cs.LG2025

RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs

Vibha Belavadi, Tushar Vatsa, Dewang Sultania +5

This paper addresses fine-tuning Large Language Models (LLMs) for function calling tasks when real user interaction data is unavailable. In digital content creation tools, where us…

cs.CL2024★ 2 cited

Orion-14B: Open-source Multilingual Large Language Models

Du Chen, Yi Huang, Xiaopu Li +7

In this study, we introduce Orion-14B, a collection of multilingual large language models with 14 billion parameters. We utilize a data scheduling approach to train a foundational…