12 citations · 31 across the 14 of their papers we have counts for
14 papers
The Role of Computing Resources in Publishing Foundation Model Research
Yuexing Hao, Yue Huang, Haoran Zhang +8
Cutting-edge research in Artificial Intelligence (AI) requires considerable resources, including Graphics Processing Units (GPUs), data, and human resources. In this paper, we eval…
Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study
Yujun Zhou, Jiayi Ye, Zipeng Ling +8
Logical reasoning is a core capability for large language models (LLMs), yet existing benchmarks that rely solely on final-answer accuracy fail to capture the quality of the reason…
SaSR-Net: Source-Aware Semantic Representation Network for Enhancing Audio-Visual Question Answering
Tianyu Yang, Yiyang Nan, Lisen Dai +3
Audio-Visual Question Answering (AVQA) is a challenging task that involves answering questions based on both auditory and visual information in videos. A significant challenge is i…
Improving LLM Reasoning through Scaling Inference Computation with Collaborative Verification
Zhenwen Liang, Ye Liu, Tong Niu +3
Despite significant advancements in the general capability of large language models (LLMs), they continue to struggle with consistent and accurate reasoning, especially in complex…
SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark
Zhenwen Liang, Kehan Guo, Gang Liu +7
The paper introduces SceMQA, a novel benchmark for scientific multimodal question answering at the college entrance level. It addresses a critical educational phase often overlooke…
Defending Jailbreak Prompts via In-Context Adversarial Game
Yujun Zhou, Yufei Han, Haomin Zhuang +4
Large Language Models (LLMs) demonstrate remarkable capabilities across diverse applications. However, concerns regarding their security, particularly the vulnerability to jailbrea…
Manipulating Predictions over Discrete Inputs in Machine Teaching
Xiaodong Wu, Yufei Han, Hayssam Dahrouj +3
Machine teaching often involves the creation of an optimal (typically minimal) dataset to help a model (referred to as the `student') achieve specific goals given by a teacher. Whi…
MinT: Boosting Generalization in Mathematical Reasoning via Multi-View Fine-Tuning
Zhenwen Liang, Dian Yu, Xiaoman Pan +4
Reasoning in mathematical domains remains a significant challenge for relatively small language models (LMs). Many current methods focus on specializing LMs in mathematical reasoni…
Improving Language Models via Plug-and-Play Retrieval Feedback
Wenhao Yu, Zhihan Zhang, Zhenwen Liang +2
Large language models (LLMs) exhibit remarkable performance across various NLP tasks. However, they often generate incorrect or hallucinated information, which hinders their practi…
Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation
Zhenwen Liang, Wenhao Yu, Tanmay Rajpurohit +3
In this paper, we present a novel approach for distilling math word problem solving capabilities from large language models (LLMs) into smaller, more efficient student models. Our…
Analogical Math Word Problems Solving with Enhanced Problem-Solution Association
Zhenwen Liang, Jipeng Zhang, Xiangliang Zhang
Math word problem (MWP) solving is an important task in question answering which requires human-like reasoning ability. Analogical reasoning has long been used in mathematical educ…
Generalizing Math Word Problem Solvers via Solution Diversification
Zhenwen Liang, Jipeng Zhang, Lei Wang +3
Current math word problem (MWP) solvers are usually Seq2Seq models trained by the (one-problem; one-solution) pairs, each of which is made of a problem description and a solution s…
Data-Driven State Estimation for Light-Emitting Diode Underwater Optical Communication
Yingquan Li, Zhenwen Liang, Ibrahima N'Doye +3
Light-Emitting Diodes (LEDs) based underwater optical wireless communications (UOWCs), a technology with low latency and high data rates, have attracted significant importance for…
MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving
Zhenwen Liang, Jipeng Zhang, Lei Wang +4
Math word problem (MWP) solving faces a dilemma in number representation learning. In order to avoid the number representation issue and reduce the search space of feasible solutio…