activity
20162025
most citedMeasuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological View

80 citations · 557 across the 56 of their papers we have counts for

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Showing 2024 · cs.CLShow all

8 papers · 2 filters

cs.CL2024

StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models

Zhicheng Guo, Sijie Cheng, Hao Wang +6

Large Language Models (LLMs) have witnessed remarkable advancements in recent years, prompting the exploration of tool learning, which integrates LLMs with external tools to addres…

cs.CL2024

Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models

Xiaolong Wang, Yile Wang, Yuanchi Zhang +4

Large Language Models (LLMs) have achieved remarkable performance in objective tasks such as open-domain question answering and mathematical reasoning, which can often be solved th…

cs.CL2024

Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages

Yuanchi Zhang, Yile Wang, Zijun Liu +5

While large language models (LLMs) have been pre-trained on multilingual corpora, their performance still lags behind in most languages compared to a few resource-rich languages. O…

cs.CL2024★ 1 cited

DEEM: Dynamic Experienced Expert Modeling for Stance Detection

Xiaolong Wang, Yile Wang, Sijie Cheng +2

Recent work has made a preliminary attempt to use large language models (LLMs) to solve the stance detection task, showing promising results. However, considering that stance detec…

cs.CL2024

PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs

An Liu, Zonghan Yang, Zhenhe Zhang +6

While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-sp…

cs.CL2024

Browse and Concentrate: Comprehending Multimodal Content via prior-LLM Context Fusion

Ziyue Wang, Chi Chen, Yiqi Zhu +7

With the bloom of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) that incorporate LLMs with pre-trained vision models have recently demonstrated impressive…

cs.CL2024

Enabling Weak LLMs to Judge Response Reliability via Meta Ranking

Zijun Liu, Boqun Kou, Peng Li +4

Despite the strong performance of large language models (LLMs) across a wide range of tasks, they still have reliability issues. Previous studies indicate that strong LLMs like GPT…

cs.CL2024

Speak It Out: Solving Symbol-Related Problems with Symbol-to-Language Conversion for Language Models

Yile Wang, Sijie Cheng, Zixin Sun +2

Symbols (or more broadly, non-natural language textual representations) such as numerical sequences, molecular formulas, and table delimiters widely exist, playing important roles…