18 citations · 20 across the 18 of their papers we have counts for
17 papers · 1 filter
CollageAttack: Exploiting Cross-Modal Alignment Flaws in T2I Models through Spatial Text Composition
Zhiyi Mou, Yao Lu, Wangze Ni +6
Text-to-image (T2I) models have substantially improved in language understanding, in-image text rendering, and visual composition, while their safety mechanisms do not always keep…
Exploiting Residual Reachability for Cross-Model Migration of Graph-Based Indexes in Approximate Nearest Neighbor Search
Baoyuan Gu, Xiaoyao Zhong, Jiabao Jin +5
Approximate nearest neighbor search (ANNS) underpins large-scale vector retrieval in search, recommendation, and retrieval-augmented generation. Graph-based indexes have demonstrat…
Beyond Final Decisions: A Process-Centric Benchmark for Transparent AI-Assisted Peer Review
Siming Yuan, Xueyi Zhang, Wangze Ni +7
Peer review is central to quality control in science. However, existing evaluations of AI-assisted peer review mainly focus on the overall quality of generated reviews or the accur…
MERIT: Efficient In-Place Deletion for Dynamic Graph-Based Approximate Nearest Neighbor Indexes
Zekai Wu, Jiabao Jin, Peng Cheng +6
Graph-based indexes have become the dominant approach to approximate nearest neighbor search (ANNS) over high-dimensional data and play a crucial role in real-world applications su…
QV-PIC: Query-Aware Visual Position-Independent Caching for Efficient RAG Serving
Yilin Liu, Rui Meng, Wangze Ni +5
Retrieval-Augmented Generation (RAG) repeatedly prefills identical text chunks across queries, incurring redundant computations. Position-Independent Caching (PIC) mitigates it by…
DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution
Hanghui Guo, Weijie Shi, Zhangze Chen +6
Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort. Therefore, recent research has i…
ActBench: Self-Evolving Benchmark of Behavioral Safety in Cowork Agents
Hongwei Yao, Yiming Liu, Meihui Chen +6
Cowork agents may complete benign tasks while disclosing protected data, manipulating unauthorized state, invocate unauthorized API. We define behavioral safety and introduce ActBe…
From Role Prompt to Infinite Thinking: Exploiting Persona Conditioning for Inference Cost Attacks in LLMs
Zhiyi Mou, Wangze Ni, Tianfang Xiao +6
LLMs are increasingly deployed in real-world applications, making inference efficiency and service reliability critical concerns due to their substantial computational costs. Howev…
QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving
Jianxin Yan, Wangze Ni, Zhenxin Li +8
Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing retrieved contexts makes the pr…
Beyond Retrieval: Learning Compact User Representations for Scalable LLM Personalization
Heng Cao, Fan Zhang, Jian Yao +8
Personalizing large language models requires adapting model behavior to individual users while preserving robustness and deployment-scale efficiency. Existing approaches typically…
TravelEval: A Comprehensive Benchmarking Framework for Evaluating LLM-Powered Travel Planning Agents
Weiyi Chen, Shuaixiong Wang, Ziyun Gao +5
The development of Large Language Models (LLMs) has significantly improved travel planning applications, yet evaluating such models is limited by existing benchmarks' limitations:…
When AI reviews science: Can we trust the referee?
Jialiang Wang, Yuchen Liu, Hang Xu +7
The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large langu…
SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models
Jianhong Li, Zeheng Qian, Wangze Ni +4
LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lacking due to the limitations of…
QCFuse: Query-Centric Cache Fusion for Efficient RAG Inference
Jianxin Yan, Zeheng Qian, Wangze Ni +6
Cache fusion accelerates generation process of LLMs equipped with RAG through KV caching and selective token recomputation, thereby reducing computational costs and improving effic…
RAC: Relation-Aware Cache Replacement for Large Language Models
Yuchong Wu, Zihuan Xu, Wangze Ni +5
The scaling of Large Language Model (LLM) services faces significant cost and latency challenges, making effective caching under tight capacity crucial. Existing cache replacement…
RxnNano:Training Compact LLMs for Chemical Reaction and Retrosynthesis Prediction via Hierarchical Curriculum Learning
Ran Li, Shimin Di, Haowei LI +4
Chemical reaction prediction is pivotal for accelerating drug discovery and synthesis planning. Despite advances in data-driven models, current approaches are hindered by an overem…
SpatialJB: How Text Distribution Art Becomes the "Jailbreak Key" for LLM Guardrails
Zhiyi Mou, Jingyuan Yang, Zeheng Qian +6
While Large Language Models (LLMs) have powerful capabilities, they remain vulnerable to jailbreak attacks, which is a critical barrier to their safe web real-time application. Cur…