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20162024
most citedLearning to Draw Samples with Amortized Stein Variational Gradient Descent

29 citations · 175 across the 25 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL2023★ 5 cited

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Weiran Yao, Shelby Heinecke, Juan Carlos Niebles +12

Recent months have seen the emergence of a powerful new trend in which large language models (LLMs) are augmented to become autonomous language agents capable of performing objecti…

cs.CL2023★ 1 cited

Preference-grounded Token-level Guidance for Language Model Fine-tuning

Shentao Yang, Shujian Zhang, Congying Xia +3

Aligning language models (LMs) with preferences is an important problem in natural language generation. A key challenge is that preferences are typically provided at the sequence l…

cs.CL2023★ 6 cited

Fantastic Rewards and How to Tame Them: A Case Study on Reward Learning for Task-oriented Dialogue Systems

Yihao Feng, Shentao Yang, Shujian Zhang +4

When learning task-oriented dialogue (ToD) agents, reinforcement learning (RL) techniques can naturally be utilized to train dialogue strategies to achieve user-specific goals. Pri…

cs.CL2021★ 2 cited

Unsupervised Out-of-Domain Detection via Pre-trained Transformers

Keyang Xu, Tongzheng Ren, Shikun Zhang +2

Deployed real-world machine learning applications are often subject to uncontrolled and even potentially malicious inputs. Those out-of-domain inputs can lead to unpredictable outp…

cs.CL2021★ 3 cited

Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System

Congying Xia, Wenpeng Yin, Yihao Feng +1

Text classification is usually studied by labeling natural language texts with relevant categories from a predefined set. In the real world, new classes might keep challenging the…