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20242026
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cs.CL2026

Revisiting the Shape Convention of Transformer Language Models

Feng-Ting Liao, Meng-Hsi Chen, Guan-Ting Yi +1

Dense Transformer language models have largely adhered to one consistent architectural shape: each layer consists of an attention module followed by a feed-forward network (FFN) wi…

cs.CL2025

RISE: Reasoning Enhancement via Iterative Self-Exploration in Multi-hop Question Answering

Bolei He, Xinran He, Mengke Chen +3

Large Language Models (LLMs) excel in many areas but continue to face challenges with complex reasoning tasks, such as Multi-Hop Question Answering (MHQA). MHQA requires integratin…

cs.CL2025

The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models

Zhivar Sourati, Farzan Karimi-Malekabadi, Meltem Ozcan +7

Language is far more than a communication tool; it encodes a wealth of information about a person's identity, psychological state, and social context, providing valuable insights f…

cs.CL2025

The Breeze 2 Herd of Models: Traditional Chinese LLMs Based on Llama with Vision-Aware and Function-Calling Capabilities

MediaTek Research, :, Chan-Jan Hsu +6

Llama-Breeze2 (hereinafter referred to as Breeze2) is a suite of advanced multi-modal language models, available in 3B and 8B parameter configurations, specifically designed to enh…

cs.CL2024

CultureLLM: Incorporating Cultural Differences into Large Language Models

Cheng Li, Mengzhou Chen, Jindong Wang +2

Large language models (LLMs) are reported to be partial to certain cultures owing to the training data dominance from the English corpora. Since multilingual cultural data are ofte…