12 citations · 26 across the 8 of their papers we have counts for
8 papers
SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents
Ziao Zhang, Kou Shi, Shiting Huang +13
As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…
Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs
Yu Li, Xiaoran Shang, Qizhi Pei +11
Post-training data plays a pivotal role in shaping the capabilities of Large Language Models (LLMs), yet datasets are often treated as isolated artifacts, overlooking the systemic…
Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models
Shun Zou, Yong Wang, Zehui Chen +4
Diffusion Large Language Models (dLLMs) have recently become a promising alternative to autoregressive large language models (ARMs). Semi-autoregressive (Semi-AR) decoding is widel…
MindSearch: Mimicking Human Minds Elicits Deep AI Searcher
Zehui Chen, Kuikun Liu, Qiuchen Wang +4
Information seeking and integration is a complex cognitive task that consumes enormous time and effort. Inspired by the remarkable progress of Large Language Models, recent works a…
Are We on the Right Way for Evaluating Large Vision-Language Models?
Lin Chen, Jinsong Li, Xiaoyi Dong +8
Large vision-language models (LVLMs) have recently achieved rapid progress, sparking numerous studies to evaluate their multi-modal capabilities. However, we dig into current evalu…
Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models
Zehui Chen, Kuikun Liu, Qiuchen Wang +5
Open-sourced Large Language Models (LLMs) have achieved great success in various NLP tasks, however, they are still far inferior to API-based models when acting as agents. How to i…
T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step
Zehui Chen, Weihua Du, Wenwei Zhang +8
Large language models (LLM) have achieved remarkable performance on various NLP tasks and are augmented by tools for broader applications. Yet, how to evaluate and analyze the tool…
ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
Lin Chen, Jinsong Li, Xiaoyi Dong +5
In the realm of large multi-modal models (LMMs), efficient modality alignment is crucial yet often constrained by the scarcity of high-quality image-text data. To address this bott…