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20232026
most citedFrom Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence

1 citations · 2 across the 16 of their papers we have counts for

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10 papers · 1 filter

cs.CL2026

Cache-Aware Joint Router Adaptation for Memory-Efficient MoE Inference

Zhenhe Wu, Yaping Jin, Qinghua Xing +6

Mixture-of-Experts (MoE) models activate few experts per token, yet their full expert sets can exceed GPU memory and require repeated weight transfers during decoding. We formulate…

cs.CL2026

A Large-Scale Multi-Dimensional Empirical Study of LLMs for Conversation Summarization

Weixiao Zhou, Gengyao Li, Junnan Zhu +3

Despite the significant advancement of LLMs in conversation summarization, their evaluation remains limited by insufficient scenarios, input lengths, and sample sizes. Furthermore,…

cs.CL2026

NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents

Jingzhe Ding, Shengda Long, Changxin Pu +46

Recent advances in coding agents suggest rapid progress toward autonomous software development, yet existing benchmarks fail to rigorously evaluate the long-horizon capabilities re…

cs.CL2025

M3TQA: Massively Multilingual Multitask Table Question Answering

Daixin Shu, Jian Yang, Zhenhe Wu +11

Tabular data is a fundamental component of real-world information systems, yet most research in table understanding remains confined to English, leaving multilingual comprehension…

cs.CL2025

P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark

Tao Sun, Enhao Pan, Zhengkai Yang +8

Academic posters are vital for scholarly communication, yet their manual creation is time-consuming. However, automated academic poster generation faces significant challenges in p…

cs.CL2025

What Are They Talking About? A Benchmark of Knowledge-Grounded Discussion Summarization

Weixiao Zhou, Junnan Zhu, Gengyao Li +4

Traditional dialogue summarization primarily focuses on dialogue content, assuming it comprises adequate information for a clear summary. However, this assumption often fails for d…

cs.CL2025

SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models

Xianfu Cheng, Wei Zhang, Shiwei Zhang +16

The increasing application of multi-modal large language models (MLLMs) across various sectors have spotlighted the essence of their output reliability and accuracy, particularly t…

cs.CL2024

TableBench: A Comprehensive and Complex Benchmark for Table Question Answering

Xianjie Wu, Jian Yang, Linzheng Chai +10

Recent advancements in Large Language Models (LLMs) have markedly enhanced the interpretation and processing of tabular data, introducing previously unimaginable capabilities. Desp…

cs.CL2024

XFormParser: A Simple and Effective Multimodal Multilingual Semi-structured Form Parser

Xianfu Cheng, Hang Zhang, Jian Yang +9

In the domain of Document AI, parsing semi-structured image form is a crucial Key Information Extraction (KIE) task. The advent of pre-trained multimodal models significantly empow…

cs.CL2023★ 1 cited

Multi-Stage Pre-training Enhanced by ChatGPT for Multi-Scenario Multi-Domain Dialogue Summarization

Weixiao Zhou, Gengyao Li, Xianfu Cheng +4

Dialogue summarization involves a wide range of scenarios and domains. However, existing methods generally only apply to specific scenarios or domains. In this study, we propose a…