5 citations · 12 across the 21 of their papers we have counts for
10 papers · 1 filter
LLM DNA: Tracing Model Evolution via Functional Representations
Zhaomin Wu, Haodong Zhao, Ziyang Wang +3
The explosive growth of large language models (LLMs) has created a vast but opaque landscape: millions of models exist, yet their evolutionary relationships through fine-tuning, di…
Beyond Brainstorming: What Drives High-Quality Scientific Ideas? Lessons from Multi-Agent Collaboration
Nuo Chen, Yicheng Tong, Jiaying Wu +5
While AI agents show potential in scientific ideation, most existing frameworks rely on single-agent refinement, limiting creativity due to bounded knowledge and perspective. Inspi…
Position: The Current AI Conference Model is Unsustainable! Diagnosing the Crisis of Centralized AI Conference
Nuo Chen, Moming Duan, Andre Huikai Lin +3
Artificial Intelligence (AI) conferences are essential for advancing research, sharing knowledge, and fostering academic community. However, their rapid expansion has rendered the…
Towards Evaluting Fake Reasoning Bias in Language Models
Qian Wang, Zhenheng Tang, Zhanzhi Lou +3
Large Reasoning Models (LRMs), evolved from standard Large Language Models (LLMs), are increasingly utilized as automated judges because of their explicit reasoning processes. Yet…
XtraGPT: Context-Aware and Controllable Academic Paper Revision via Human-AI Collaboration
Nuo Chen, Andre Lin HuiKai, Jiaying Wu +5
Despite the growing adoption of large language models (LLMs) in academic workflows, their capabilities remain limited in supporting high-quality scientific writing. Most existing s…
Assessing Judging Bias in Large Reasoning Models: An Empirical Study
Qian Wang, Zhanzhi Lou, Zhenheng Tang +5
Large Reasoning Models (LRMs) like DeepSeek-R1 and OpenAI-o1 have demonstrated remarkable reasoning capabilities, raising important questions about their biases in LLM-as-a-judge s…
JudgeLRM: Large Reasoning Models as a Judge
Nuo Chen, Zhiyuan Hu, Qingyun Zou +4
Large Language Models (LLMs) are increasingly adopted as evaluators, offering a scalable alternative to human annotation. However, existing supervised fine-tuning (SFT) approaches…
From ChatGPT to DeepSeek: Can LLMs Simulate Humanity?
Qian Wang, Zhenheng Tang, Bingsheng He
Simulation powered by Large Language Models (LLMs) has become a promising method for exploring complex human social behaviors. However, the application of LLMs in simulations prese…
The Lottery LLM Hypothesis, Rethinking What Abilities Should LLM Compression Preserve?
Zhenheng Tang, Xiang Liu, Qian Wang +4
Motivated by reducing the computational and storage costs of LLMs, model compression and KV cache compression have attracted much attention from researchers. However, current metho…
LLM-based Human Simulations Have Not Yet Been Reliable
Qian Wang, Jiaying Wu, Zichen Jiang +6
Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current LLM-based human simulations rema…