12 citations · 18 across the 4 of their papers we have counts for
4 papers
CodecLM: Aligning Language Models with Tailored Synthetic Data
Zifeng Wang, Chun-Liang Li, Vincent Perot +5
Instruction tuning has emerged as the key in aligning large language models (LLMs) with specific task instructions, thereby mitigating the discrepancy between the next-token predic…
Noise-Aware Training of Layout-Aware Language Models
Ritesh Sarkhel, Xiaoqi Ren, Lauro Beltrao Costa +5
A visually rich document (VRD) utilizes visual features along with linguistic cues to disseminate information. Training a custom extractor that identifies named entities from a doc…
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li +8
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat…
Learning to Prompt for Continual Learning
Zifeng Wang, Zizhao Zhang, Chen-Yu Lee +7
The mainstream paradigm behind continual learning has been to adapt the model parameters to non-stationary data distributions, where catastrophic forgetting is the central challeng…