most citedWhen Reasoning Meets Information Aggregation: A Case Study with Sports Narratives

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

A Versatile Multimodal Agent for Multimedia Content Generation

Daoan Zhang, Wenlin Yao, Xiaoyang Wang +3

With the advancement of AIGC (AI-generated content) technologies, an increasing number of generative models are revolutionizing fields such as video editing, music generation, and…

cs.CL2024

Router-Tuning: A Simple and Effective Approach for Enabling Dynamic-Depth in Transformers

Shwai He, Tao Ge, Guoheng Sun +3

Traditional transformer models often allocate a fixed amount of computational resources to every input token, leading to inefficient and unnecessary computation. To address this, t…

cs.CL2024

DeFine: Decision-Making with Analogical Reasoning over Factor Profiles

Yebowen Hu, Xiaoyang Wang, Wenlin Yao +5

LLMs are ideal for decision-making thanks to their ability to reason over long contexts. However, challenges arise when processing speech transcripts that describe complex scenario…

cs.CL2024★ 1 cited

When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives

Yebowen Hu, Kaiqiang Song, Sangwoo Cho +5

Reasoning is most powerful when an LLM accurately aggregates relevant information. We examine the critical role of information aggregation in reasoning by requiring the LLM to anal…

cs.CL2024

Polarity Calibration for Opinion Summarization

Yuanyuan Lei, Kaiqiang Song, Sangwoo Cho +3

Opinion summarization is automatically generating summaries from a variety of subjective information, such as product reviews or political opinions. The challenge of opinions summa…

cs.CL2024

Can Large Language Models do Analytical Reasoning?

Yebowen Hu, Kaiqiang Song, Sangwoo Cho +4

This paper explores the cutting-edge Large Language Model with analytical reasoning on sports. Our analytical reasoning embodies the tasks of letting large language models count ho…

cs.CL2024

SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs

Yebowen Hu, Kaiqiang Song, Sangwoo Cho +4

Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and…

cs.CL2024

SPECTRUM: Speaker-Enhanced Pre-Training for Long Dialogue Summarization

Sangwoo Cho, Kaiqiang Song, Chao Zhao +2

Multi-turn dialogues are characterized by their extended length and the presence of turn-taking conversations. Traditional language models often overlook the distinct features of t…