activity
20242026
most citedBEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search

2 citations · 5 across the 14 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 2 cited

BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search

Linzhuang Sun, Hao Liang, Jingxuan Wei +4

Large Language Models (LLMs) have exhibited exceptional performance across a broad range of tasks and domains. However, they still encounter difficulties in solving mathematical pr…

cs.CL2024

Synth-Empathy: Towards High-Quality Synthetic Empathy Data

Hao Liang, Linzhuang Sun, Jingxuan Wei +5

In recent years, with the rapid advancements in large language models (LLMs), achieving excellent empathetic response capabilities has become a crucial prerequisite. Consequently,…

cs.CV2024★ 1 cited

KeyVideoLLM: Towards Large-scale Video Keyframe Selection

Hao Liang, Jiapeng Li, Tianyi Bai +7

Recently, with the rise of web videos, managing and understanding large-scale video datasets has become increasingly important. Video Large Language Models (VideoLLMs) have emerged…

cs.CV2024

MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts

Hao Liang, Linzhuang Sun, Minxuan Zhou +7

With the rapid progress of Multimodal LLMs, evaluating their mathematical reasoning capabilities has become an increasingly important research direction. In particular, visual-text…

cs.CL2024★ 1 cited

Efficient-Empathy: Towards Efficient and Effective Selection of Empathy Data

Linzhuang Sun, Hao Liang, Jingxuan Wei +4

In recent years, with the rapid advancements in large language models (LLMs), achieving excellent empathetic response capability has become a crucial prerequisite. Consequently, ma…