1 citations · 2 across the 7 of their papers we have counts for
9 papers
Beyond Binary Labels: Diagnostic Evaluation of LLM Safety with Prompt-Level Rubrics
Hongyu Li, Xinlong Huang, Zhan Yu +13
Current LLM safety benchmarks predominantly rely on binary safe or unsafe labels, lacking explanatory depth and suffering from low consistency across automated judges. To address t…
Elo-Evolve: A Co-evolutionary Framework for Language Model Alignment
Jing Zhao, Ting Zhen, Junwei Bao +2
Current alignment methods for Large Language Models (LLMs) rely on compressing vast amounts of human preference data into static, absolute reward functions, leading to data scarcit…
KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
Xindi Luo, Zequn Sun, Jing Zhao +2
Parameter-efficient finetuning (PEFT) is a key technique for adapting large language models (LLMs) to downstream tasks. In this paper, we study leveraging knowledge graph embedding…
PLM: Probabilistically Permuted Prophet Language Modeling for Generative Pre-Training
Junwei Bao, Yifan Wang, Jiangyong Ying +4
Conventional autoregressive left-to-right (L2R) sequence generation faces two issues during decoding: limited to unidirectional target sequence modeling, and constrained on strong…
LUNA: Learning Slot-Turn Alignment for Dialogue State Tracking
Yifan Wang, Jing Zhao, Junwei Bao +3
Dialogue state tracking (DST) aims to predict the current dialogue state given the dialogue history. Existing methods generally exploit the utterances of all dialogue turns to assi…
OPERA:Operation-Pivoted Discrete Reasoning over Text
Yongwei Zhou, Junwei Bao, Chaoqun Duan +7
Machine reading comprehension (MRC) that requires discrete reasoning involving symbolic operations, e.g., addition, sorting, and counting, is a challenging task. According to this…
Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT
Jing Zhao, Yifan Wang, Junwei Bao +2
Transformer-based pre-trained models, such as BERT, have shown extraordinary success in achieving state-of-the-art results in many natural language processing applications. However…
RoR: Read-over-Read for Long Document Machine Reading Comprehension
Jing Zhao, Junwei Bao, Yifan Wang +4
Transformer-based pre-trained models, such as BERT, have achieved remarkable results on machine reading comprehension. However, due to the constraint of encoding length (e.g., 512…
SGG: Learning to Select, Guide, and Generate for Keyphrase Generation
Jing Zhao, Junwei Bao, Yifan Wang +3
Keyphrases, that concisely summarize the high-level topics discussed in a document, can be categorized into present keyphrase which explicitly appears in the source text, and absen…