3 citations · 6 across the 9 of their papers we have counts for
9 papers
Enhanced Language Model Truthfulness with Learnable Intervention and Uncertainty Expression
Farima Fatahi Bayat, Xin Liu, H. V. Jagadish +1
Large language models (LLMs) can generate long-form and coherent text, yet they often hallucinate facts, which undermines their reliability. To mitigate this issue, inference-time…
Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding
Xin Liu, Farima Fatahi Bayat, Lu Wang
Calibrating language models (LMs) aligns their generation confidence with the actual likelihood of answer correctness, which can inform users about LMs' reliability and mitigate ha…
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models
Xiaoyue Wang, Xin Liu, Lijie Wang +3
As commonly-used methods for debiasing natural language understanding (NLU) models, dataset refinement approaches heavily rely on manual data analysis, and thus maybe unable to cov…
LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
Xin Liu, Muhammad Khalifa, Lu Wang
A model is considered well-calibrated when its probability estimate aligns with the actual likelihood of the output being correct. Calibrating language models (LMs) is crucial, as…
A Simple yet Effective Self-Debiasing Framework for Transformer Models
Xiaoyue Wang, Lijie Wang, Xin Liu +3
Current Transformer-based natural language understanding (NLU) models heavily rely on dataset biases, while failing to handle real-world out-of-distribution (OOD) instances. Many m…
BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases
Xin Liu, Muhammad Khalifa, Lu Wang
Energy-based models (EBMs) have gained popularity for controlled text generation due to their high applicability to a wide range of constraints. However, sampling from EBMs is non-…
Getting the Most out of Simile Recognition
Xiaoyue Wang, Linfeng Song, Xin Liu +2
Simile recognition involves two subtasks: simile sentence classification that discriminates whether a sentence contains simile, and simile component extraction that locates the cor…
KGR^4: Retrieval, Retrospect, Refine and Rethink for Commonsense Generation
Xin Liu, Dayiheng Liu, Baosong Yang +6
Generative commonsense reasoning requires machines to generate sentences describing an everyday scenario given several concepts, which has attracted much attention recently. Howeve…
Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation
Xin Liu, Baosong Yang, Dayiheng Liu +5
A well-known limitation in pretrain-finetune paradigm lies in its inflexibility caused by the one-size-fits-all vocabulary. This potentially weakens the effect when applying pretra…