8 citations · 14 across the 10 of their papers we have counts for
12 papers
SPECMEM: Accelerating Agentic Tool Calling via Live Memory Management
Zihe Song, Wenting Zhao, Ye Liu +4
Tool-calling agents are mostly optimized for accuracy; in deployment, however, their growing cost is latency: every tool call is decoded autoregressively. Speculative decoding acce…
FinHarness: An Inline Lifecycle Safety Harness for Finance LLM Agents
Haoxuan Jia, Yang Liu, Bin Chong +10
Finance LLM agents must simultaneously block prompt-induced unauthorized actions and approve legitimate multi-step business workflows. However, boundary filters often miss irrevers…
ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomies
Shang Luo, Yingguang Yang, Zhenchen Sun +8
The democratization of LLMs has accelerated the generation and circulation of highly fluent disinformation, making traditional syntax-semantic verification increasingly insufficien…
Why LLMs Hallucinate on Structured Knowledge: A Mechanistic Analysis of Reasoning over Linearized Representations
Shanghao Li, Jinda Han, Yibo Wang +5
In many reasoning tasks, large language models (LLMs) rely on structured external knowledge, such as graphs and tables, which is typically linearized into sequential token represen…
SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness
Jiahao Huo, Wenjie Qu, Yibo Yan +5
Semantic-level watermarking (SWM) improves robustness against text modifications by treating sentences as the basic unit. However, robustness to paragraph-level paraphrasing remain…
Detecting Hallucinations in Graph Retrieval-Augmented Generation via Attention Patterns and Semantic Alignment
Shanghao Li, Jinda Han, Yibo Wang +5
Graph-based Retrieval-Augmented Generation (GraphRAG) enhances Large Language Models (LLMs) by incorporating external knowledge from linearized subgraphs retrieved from knowledge g…
MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms
Yibo Wang, Congying Xia, Wenting Zhao +5
Unit test generation has become a promising and important Large Language Model (LLM) use case. However, existing evaluation benchmarks for LLM unit test generation focus on functio…
Disclosure and Mitigation of Gender Bias in LLMs
Xiangjue Dong, Yibo Wang, Philip S. Yu +1
Large Language Models (LLMs) can generate biased responses. Yet previous direct probing techniques contain either gender mentions or predefined gender stereotypes, which are challe…
Aspect-based Meeting Transcript Summarization: A Two-Stage Approach with Weak Supervision on Sentence Classification
Zhongfen Deng, Seunghyun Yoon, Trung Bui +7
Aspect-based meeting transcript summarization aims to produce multiple summaries, each focusing on one aspect of content in a meeting transcript. It is challenging as sentences rel…
JPAVE: A Generation and Classification-based Model for Joint Product Attribute Prediction and Value Extraction
Zhongfen Deng, Hao Peng, Tao Zhang +4
Product attribute value extraction is an important task in e-Commerce which can help several downstream applications such as product search and recommendation. Most previous models…
: A Distribution-Aware Adversarial Attack against Language Models
Yibo Wang, Xiangjue Dong, James Caverlee +1
Language models can be manipulated by adversarial attacks, which introduce subtle perturbations to input data. While recent attack methods can achieve a relatively high attack succ…
Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation
Xiangjue Dong, Yibo Wang, Philip S. Yu +1
Large Language Models (LLMs) can generate biased and toxic responses. Yet most prior work on LLM gender bias evaluation requires predefined gender-related phrases or gender stereot…