24 citations · 54 across the 30 of their papers we have counts for
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cs.CL2024
EscapeBench: Towards Advancing Creative Intelligence of Language Model Agents
Cheng Qian, Peixuan Han, Qinyu Luo +9
Language model agents excel in long-session planning and reasoning, but existing benchmarks primarily focus on goal-oriented tasks with explicit objectives, neglecting creative ada…
cs.CL2024
The Right Time Matters: Data Arrangement Affects Zero-Shot Generalization in Instruction Tuning
Bingxiang He, Ning Ding, Cheng Qian +10
Understanding alignment techniques begins with comprehending zero-shot generalization brought by instruction tuning, but little of the mechanism has been understood. Existing work…
cs.CL2024★ 4 cited
Tell Me More! Towards Implicit User Intention Understanding of Language Model Driven Agents
Cheng Qian, Bingxiang He, Zhong Zhuang +8
Current language model-driven agents often lack mechanisms for effective user participation, which is crucial given the vagueness commonly found in user instructions. Although adep…