4 papers
Rethinking Length-Based Training: Batch Composition and Loss Normalization in Speech Token Language Models
Hongjin Song, Runwu Shi, Weiqiao Shan +4
Short-to-long training is a simple curriculum for speech models, but its gains can be difficult to interpret. In speech token language models, length-based training can change the…
CASCADE Against Jailbreaks: Combination Across Stages with Controlled Attack-Defense Evaluation
Jiale Luo, Eric Han
Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, but it remains unclear which de…
Locality Matters for Training-Free Audio Token Compression in Audio-Language Models
Jiale Luo, Xiaoyu Liang, Haoji Hu
Audio-language models (ALMs) are increasingly used for audio captioning, question answering, and open-ended audio understanding, but their inference cost remains high when audio in…
Learn Before Represent: Bridging Generative and Contrastive Learning for Domain-Specific LLM Embeddings
Xiaoyu Liang, Yuchen Peng, Jiale Luo +3
Large Language Models (LLMs) adapted via contrastive learning excel in general representation learning but struggle in vertical domains like chemistry and law, primarily due to a l…