4 citations · 5 across the 12 of their papers we have counts for
7 papers · 1 filter
Taming the Thinker: Conditional Entropy Shaping for Adaptive LLM Reasoning
Shuyu Wei, Jian Sun, Delai Qiu +6
Entropy-based deep reasoning has emerged as a promising direction for improving the reasoning capabilities of Large Language Models (LLMs), but existing methods often either increa…
LaTER: Efficient Test-Time Reasoning via Latent Exploration and Explicit Verification
Xuan Li, Yining Wang, Yuchen Liu +7
Chain-of-thought (CoT) reasoning improves large language models (LLMs) on difficult tasks, but it also makes inference expensive because every intermediate step must be generated a…
Zipper-LoRA: Dynamic Parameter Decoupling for Speech-LLM based Multilingual Speech Recognition
Yuxiang Mei, Delai Qiu, Shengping Liu +2
Speech Large Language Models (Speech-LLMs) have emerged as a powerful approach for automatic speech recognition (ASR) by aligning speech encoders with large language models. Howeve…
ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework
Ao Chang, Tong Zhou, Yubo Chen +4
Legal Judgment Prediction (LJP) aims to predict judicial outcomes, including relevant legal charge, terms, and fines, which is a crucial process in Large Language Model(LLM). Howev…
Semantic Pivots Enable Cross-Lingual Transfer in Large Language Models
Kaiyu He, Tong Zhou, Yubo Chen +4
Large language models (LLMs) demonstrate remarkable ability in cross-lingual tasks. Understanding how LLMs acquire this ability is crucial for their interpretability. To quantify t…
Transparentize the Internal and External Knowledge Utilization in LLMs with Trustworthy Citation
Jiajun Shen, Tong Zhou, Yubo Chen +4
While hallucinations of large language models could been alleviated through retrieval-augmented generation and citation generation, how the model utilizes internal knowledge is sti…
Knowledge Guided Metric Learning for Few-Shot Text Classification
Dianbo Sui, Yubo Chen, Binjie Mao +3
The training of deep-learning-based text classification models relies heavily on a huge amount of annotation data, which is difficult to obtain. When the labeled data is scarce, mo…