7 citations · 13 across the 13 of their papers we have counts for
6 papers · 1 filter
EgoLCD: Egocentric Video Generation with Long Context Diffusion
Liuzhou Zhang, Jiarui Ye, Yuanlei Wang +6
Generating long, coherent egocentric videos is difficult, as hand-object interactions and procedural tasks require reliable long-term memory. Existing autoregressive models suffer…
Long-Context Attention Benchmark: From Kernel Efficiency to Distributed Context Parallelism
Tao Bu, Qiangang Wang, Bowen Zeng +4
Transformer-based large language models (LLMs) have achieved remarkable success, yet their standard attention mechanism incurs quadratic computation and memory costs with respect t…
: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation
Hao Wang, Linlong Xu, Heng Liu +11
Aligning Large Language Models (LLMs) with human preferences is pivotal for Machine Translation (MT), yet current approaches are often hindered by misleading reward signals. Our an…
Marco-Bench-MIF: On Multilingual Instruction-Following Capability of Large Language Models
Bo Zeng, Chenyang Lyu, Sinuo Liu +14
Instruction-following capability has become a major ability to be evaluated for Large Language Models (LLMs). However, existing datasets, such as IFEval, are either predominantly m…
RODS: Robust Optimization Inspired Diffusion Sampling for Detecting and Reducing Hallucination in Generative Models
Yiqi Tian, Pengfei Jin, Mingze Yuan +3
Diffusion models have achieved state-of-the-art performance in generative modeling, yet their sampling procedures remain vulnerable to hallucinations-often stemming from inaccuraci…
Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models
Huifeng Yin, Yu Zhao, Minghao Wu +9
Large Reasoning Models(LRMs) such as OpenAI o1 and DeepSeek-R1 have shown remarkable reasoning capabilities by scaling test-time compute and generating long Chain-of-Thought(CoT).…