7 citations · 39 across the 30 of their papers we have counts for
6 papers · 2 filters
On the Zero-Shot Generalization of Machine-Generated Text Detectors
Xiao Pu, Jingyu Zhang, Xiaochuang Han +2
The rampant proliferation of large language models, fluent enough to generate text indistinguishable from human-written language, gives unprecedented importance to the detection of…
KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models
Yuyang Bai, Shangbin Feng, Vidhisha Balachandran +4
Large language models (LLMs) demonstrate remarkable performance on knowledge-intensive tasks, suggesting that real-world knowledge is encoded in their model parameters. However, be…
SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation
Abe Bohan Hou, Jingyu Zhang, Tianxing He +7
Existing watermarking algorithms are vulnerable to paraphrase attacks because of their token-level design. To address this issue, we propose SemStamp, a robust sentence-level seman…
Knowledge Crosswords: Geometric Knowledge Reasoning with Large Language Models
Wenxuan Ding, Shangbin Feng, Yuhan Liu +4
We propose Knowledge Crosswords, a geometric knowledge reasoning benchmark consisting of incomplete knowledge networks bounded by structured factual constraints, where LLMs are tas…
Resolving Knowledge Conflicts in Large Language Models
Yike Wang, Shangbin Feng, Heng Wang +4
Large language models (LLMs) often encounter knowledge conflicts, scenarios where discrepancy arises between the internal parametric knowledge of LLMs and non-parametric informatio…
LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud
Mengke Zhang, Tianxing He, Tianle Wang +5
In the current user-server interaction paradigm of prompted generation with large language models (LLM) on cloud, the server fully controls the generation process, which leaves zer…