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20222026
most citedReka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models

3 citations · 6 across the 10 of their papers we have counts for

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cs.CL2026

Cognitive Enhancement: Rethinking the Necessity of Role-Playing for Large Language Models

Xingjie Zhuang, Jialong Tang, Chulun Zhou +5

Role-playing prompting has become a popular yet simple technique for improving LLM reasoning and output quality. However, whether it consistently boosts performance across diverse…

cs.CL2026

WnW: Waxing-and-Waning KV Cache for Long-Form Speech LLMs

Yiming Yao, Chenyang Lyu, Xuanfan Ni +4

Long-form audio inputs make the KV cache the dominant memory cost of speech LLMs. Prefill-only KV compression methods permanently discard audio KV positions once evicted, with no p…

cs.CL2026

ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation

Yuzhe Shang, Pengzhi Gao, Yazheng Yang +4

Large language models (LLMs) have recently demonstrated promising performance in simultaneous machine translation (SimulMT). However, applying decoder-only LLMs to SimulMT introduc…

cs.CL2025

Cognitive Alpha Mining via LLM-Driven Code-Based Evolution

Fengyuan Liu, Yi Huang, Sichun Luo +6

Discovering effective predictive signals, or "alphas," from financial data with high dimensionality and extremely low signal-to-noise ratio remains a difficult open problem. Despit…

cs.CL2025

Towards Fine-Grained Code-Switch Speech Translation with Semantic Space Alignment

Yan Gao, Yazheng Yang, Zhibin Lan +5

Code-switching (CS) speech translation (ST) aims to translate speech that alternates between multiple languages into a target language text, posing significant challenges due to th…

cs.CL2024★ 3 cited

Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models

Reka Team, Aitor Ormazabal, Che Zheng +23

We introduce Reka Core, Flash, and Edge, a series of powerful multimodal language models trained from scratch by Reka. Reka models are able to process and reason with text, images,…