1 citations · 1 across the 5 of their papers we have counts for
5 papers
Overcoming State Inertia: Minimally Invasive Temporal Alignment for Evolving Contexts
Yijun Liao
Long-context dialogue systems suffer from state inertia, where models over-attend to history and fail to adapt to evolving intents. We demonstrate that standard alignment methods l…
What-If Analysis of Large Language Models: Explore the Game World Using Proactive Thinking
Yuan Sui, Yanming Zhang, Yi Liao +5
LLMs struggle with decision-making in high-stakes environments like MOBA games, primarily due to a lack of proactive reasoning and limited understanding of complex game dynamics. T…
Think in Games: Learning to Reason in Games via Reinforcement Learning with Large Language Models
Yi Liao, Yu Gu, Yuan Sui +5
Large language models (LLMs) excel at complex reasoning tasks such as mathematics and coding, yet they frequently struggle with simple interactive tasks that young children perform…
Optimal Corpus Aware Training for Neural Machine Translation
Yi-Hsiu Liao, Cheng Shen, Brenda +1
Corpus Aware Training (CAT) leverages valuable corpus metadata during training by injecting corpus information into each training example, and has been found effective in the liter…
SoftDedup: an Efficient Data Reweighting Method for Speeding Up Language Model Pre-training
Nan He, Weichen Xiong, Hanwen Liu +6
The effectiveness of large language models (LLMs) is often hindered by duplicated data in their extensive pre-training datasets. Current approaches primarily focus on detecting and…