8 papers
X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models
Boyu Li, Chaoyi Xu, Haoqi Yuan +5
Learning universal policies from cross-embodied data remains a fundamental challenge in robotics. Although Vision-Language-Action (VLA) models are pre-trained on large and diverse…
TANDEM: Bi-Level Data Mixture Optimization with Twin Networks
Jiaxing Wang, Deping Xiang, Jin Xu +9
The capabilities of large language models (LLMs) significantly depend on training data drawn from various domains. Optimizing domain-specific mixture ratios can be modeled as a bi-…
Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning
Wei Fan, Yining Zhou, Mufan Zhang +8
While large language models (LLMs) augmented with agentic search capabilities show promise for legal reasoning, they overlook a fundamental constraint that applicable law must matc…
Multi-Agent Coordination Adaptation via Structure-Guided Orchestration
Haoran Li, Shulun Chen, Shaoyuan Sun +1
As large language model (LLM)-based multi-agent systems scale to handle increasingly complex tasks, balancing structural stability and dynamic adaptability becomes increasingly cha…
SciCustom: A Framework for Custom Evaluation of Scientific Capabilities in Large Language Models
Yiyang Gu, Junwei Yang, Junyu Luo +15
Large language models (LLMs) are increasingly applied to scientific research, yet existing evaluations often fail to reflect the fine-grained capabilities required in practice. Mos…
Jailbreaking Large Language Models with Morality Attacks
Ying Su, Mingen Zheng, Weili Diao +1
Pluralism alignment with AI has the sophisticated and necessary goal of creating AI that can coexist with and serve morally multifaceted humanity. Research towards pluralism alignm…
GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety
Changxuan Fan, Xi Yang, Yueyuan Zheng +9
As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities from social isolation, limited…
Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
Hyunji Nam, Haoran Li, Natasha Jaques
While post-training has successfully improved large language models (LLMs) across a variety of domains, these gains heavily rely on human-labeled data or external verifiers. Existi…