24 papers
Activation-Guided Neuron Intervention to Induce Alzheimer's-Related Computational Language Phenotypes in a Large Language Model
Rui He, Ercong Nie, Hong Jiang +3
Changes in spontaneous speech provide an early signal of cognitive dysfunction in Alzheimer's disease (AD) that large language models (LLMs) can detect. However, detection alone ca…
Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents
Sikuan Yan, Ahmed Bahloul, Ercong Nie +4
Memory-augmented LLM agents enable interactions that extend beyond finite context windows by storing, updating, and reusing information across sessions. However, training such agen…
ChunkFT: Byte-Streamed Optimization for Memory-Efficient Full Fine-Tuning
Yongkang Liu, Zijing Wang, Mengjie Zhao +7
This work presents \textsc{ChunkFT}, a memory-efficient fine-tuning framework that reformulates full-parameter fine-tuning around a dynamically activated working set. \textsc{Chunk…
DiM\textsuperscript{3}: Bridging Multilingual and Multimodal Models via Direction- and Magnitude-Aware Merging
Zijing Wang, Mingyang Wang, Ercong Nie +6
Towards more general and human-like intelligence, large language models should seamlessly integrate both multilingual and multimodal capabilities; however, extending an existing mu…
PyraVid: Hierarchical Multimodal Memory for Long-Horizon Video Reasoning
Sikuan Yan, Sicheng Dong, Haotong Wang +8
Memory has become an increasingly important component of agentic systems, as these systems are expected to reason over long-term experience. However, prior work has largely focused…
Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models
Hengyuan Zhang, Zhihao Zhang, Mingyang Wang +26
Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat…