6 citations · 6 across the 3 of their papers we have counts for
3 papers · 1 filter
A Survey on Large Language Model-Based Game Agents
Sihao Hu, Tiansheng Huang, Gaowen Liu +6
Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities…
Rebellion: Noise-Robust Reasoning Training for Audio Reasoning Models
Tiansheng Huang, Virat Shejwalkar, Oscar Chang +2
Instilling reasoning capabilities in large models (LMs) using reasoning training (RT) significantly improves LMs' performances. Thus Audio Reasoning Models (ARMs), i.e., audio LMs…
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi +2
Safety aligned Large Language Models (LLMs) are vulnerable to harmful fine-tuning attacks -- a few harmful data mixed in the fine-tuning dataset can break the LLMs's safety alignme…