31 citations · 32 across the 5 of their papers we have counts for
5 papers
ReAct Meets ActRe: When Language Agents Enjoy Training Data Autonomy
Zonghan Yang, Peng Li, Ming Yan +3
Language agents have demonstrated autonomous decision-making abilities by reasoning with foundation models. Recently, efforts have been made to train language agents for performanc…
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…
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…
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…
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang +22
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming…