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FourierSampler: Unlocking Non-Autoregressive Potential in Diffusion Language Models via Frequency-Guided Generation

Intermediate

Siyang He, Qiqi Wang et al.Jan 30arXiv

Diffusion language models (dLLMs) can write text in any order, but common decoding methods still prefer left-to-right, which wastes their superpower.

#diffusion language models#non-autoregressive generation#frequency-domain analysis

MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models

Beginner

Zecheng Tang, Baibei Ji et al.Jan 17arXiv

This paper builds MemoryRewardBench, a big test that checks if reward models (AI judges) can fairly grade how other AIs manage long-term memory, not just whether their final answers are right.

#reward models#long-term memory#long-context reasoning

Self-Improving VLM Judges Without Human Annotations

Intermediate

Inna Wanyin Lin, Yushi Hu et al.Dec 2arXiv

The paper shows how a vision-language model (VLM) can train itself to be a fair judge of answers about images without using any human preference labels.

#vision-language model#VLM judge#reward model

Papers3

FourierSampler: Unlocking Non-Autoregressive Potential in Diffusion Language Models via Frequency-Guided Generation

MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models

Self-Improving VLM Judges Without Human Annotations