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20142026
most citedDistilling Task-Specific Knowledge from BERT into Simple Neural Networks

335 citations · 1.7k across the 86 of their papers we have counts for

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Showing 2025 · cs.CLShow all

7 papers · 2 filters

cs.CL2025

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation

Guoqing Luo, Iffat Maab, Lili Mou +1

While reasoning-based large language models excel at complex tasks through an internal, structured thinking process, a concerning phenomenon has emerged that such a thinking proces…

cs.CL2025

TokMem: One-Token Procedural Memory for Large Language Models

Zijun Wu, Yongchang Hao, Lili Mou

Large language models are typically controlled via prompts, which must be repeatedly re-processed for every new query and are difficult to reuse modularly. We introduce TokMem, a p…

cs.CL2025

Feeding Two Birds or Favoring One? Adequacy-Fluency Tradeoffs in Evaluation and Meta-Evaluation of Machine Translation

Behzad Shayegh, Jan-Thorsten Peter, David Vilar +4

We investigate the tradeoff between adequacy and fluency in machine translation. We show the severity of this tradeoff at the evaluation level and analyze where popular metrics fal…

cs.CL2025

KETCHUP: K-Step Return Estimation for Sequential Knowledge Distillation

Jiabin Fan, Guoqing Luo, Michael Bowling +1

We propose a novel k-step return estimation method (called KETCHUP) for Reinforcement Learning(RL)-based knowledge distillation (KD) in text generation tasks. Our idea is to induce…

cs.CL2025

Multilingual Non-Autoregressive Machine Translation without Knowledge Distillation

Chenyang Huang, Fei Huang, Zaixiang Zheng +3

Multilingual neural machine translation (MNMT) aims at using one single model for multiple translation directions. Recent work applies non-autoregressive Transformers to improve th…

cs.CL2025

A Decoding Algorithm for Length-Control Summarization Based on Directed Acyclic Transformers

Chenyang Huang, Hao Zhou, Cameron Jen +3

Length-control summarization aims to condense long texts into a short one within a certain length limit. Previous approaches often use autoregressive (AR) models and treat the leng…