8 papers
LLMs Meet Isolation Kernel: Lightweight, Learning-free Binary Embeddings for Fast Retrieval
Zhibo Zhang, Yang Xu, Kai Ming Ting +1
Large language models (LLMs) have recently enabled remarkable progress in text representation. However, their embeddings are typically high-dimensional, leading to substantial stor…
MiMIC: Mitigating Visual Modality Collapse in Universal Multimodal Retrieval While Avoiding Semantic Misalignment
Juan Li, Chuanghao Ding, Xujie Zhang +1
Universal Multimodal Retrieval (UMR) aims to map different modalities (e.g., visual and textual) into a shared embedding space for multi-modal retrieval. Existing UMR methods can b…
LAVa: Layer-wise KV Cache Eviction with Dynamic Budget Allocation
Yiqun Shen, Song Yuan, Zhengze Zhang +3
KV Cache is commonly used to accelerate LLM inference with long contexts, yet its high memory demand drives the need for cache compression. Existing compression methods, however, a…
daDPO: Distribution-Aware DPO for Distilling Conversational Abilities
Zhengze Zhang, Shiqi Wang, Yiqun Shen +5
Large language models (LLMs) have demonstrated exceptional performance across various applications, but their conversational abilities decline sharply as model size decreases, pres…
Corporate Fraud Detection in Rich-yet-Noisy Financial Graph
Shiqi Wang, Zhibo Zhang, Libing Fang +2
Corporate fraud detection aims to automatically recognize companies that conduct wrongful activities such as fraudulent financial statements or illegal insider trading. Previous le…
Mixed Preference Optimization: Reinforcement Learning with Data Selection and Better Reference Model
Qi Gou, Cam-Tu Nguyen
Large Language Models (LLMs) have become increasingly popular due to their ability to process and generate natural language. However, as they are trained on massive datasets of tex…