3 citations · 3 across the 9 of their papers we have counts for
5 papers · 1 filter
JIT-Agent: Scaling Harness Intelligence via Just-in-Time Harness Evolution
Guibin Zhang, Leo Lu, Fangzhou Xie +15
Agent capability is not determined by the model alone. The agent harness, encompassing memory management, planning strategy, action protocol, and tool/skill orchestration, can domi…
A Self-Evolving Framework for Efficient Terminal Agents via Observational Context Compression
Jincheng Ren, Siwei Wu, Yizhi Li +8
As terminal agents scale to long-horizon, multi-turn workflows, a key bottleneck is not merely limited context length, but the accumulation of noisy terminal observations in the in…
PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment
Zekun Moore Wang, Shawn Wang, Kang Zhu +5
Alignment of large language models (LLMs) involves training models on preference-contrastive output pairs to adjust their responses according to human preferences. To obtain such c…
OmniBench: Towards The Future of Universal Omni-Language Models
Yizhi Li, Yinghao Ma, Ge Zhang +20
Recent advancements in multimodal large language models (MLLMs) have aimed to integrate and interpret data across diverse modalities. However, the capacity of these models to concu…
CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark
Ge Zhang, Xinrun Du, Bei Chen +19
As the capabilities of large multimodal models (LMMs) continue to advance, evaluating the performance of LMMs emerges as an increasing need. Additionally, there is an even larger g…