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AuRA: Internalizing Audio Understanding into LLMs as LoRA
Bo Cheng, Lei Shi, Zhanyu Ma +5
Recent efforts to extend large language models (LLMs) to speech inputs typically rely on cascaded ASR-LLM pipelines, end-to-end speech-language models, or bridge/distillation-based…
State Rank Dynamics in Linear Attention LLMs
Ao Sun, Hongtao Zhang, Heng Zhou +9
Linear Attention Large Language Models (LLMs) offer a compelling recurrent formulation that compresses context into a fixed-size state matrix, enabling constant-time inference. How…
From Absolute to Relative: Rethinking Reward Shaping in Group-Based Reinforcement Learning
Wenzhe Niu, Wei He, Zongxia Xie +10
Reinforcement learning has become a cornerstone for enhancing the reasoning capabilities of Large Language Models, where group-based approaches such as GRPO have emerged as efficie…
GeoRA: Geometry-Aware Low-Rank Adaptation for RLVR
Jiaying Zhang, Lei Shi, Jiguo Li +4
Reinforcement Learning with Verifiable Rewards (RLVR) is a key paradigm for improving large-scale reasoning models. Unlike supervised fine-tuning (SFT), RLVR exhibits distinct opti…