5 papers
SoloQ: Calibration-Free Quantization for Diffusion Language Models
Donghyun Lee, Arkapravo Ghosh, Varun Manjunath +5
Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based token generation. However, th…
Beyond Confidence: Test-Time Scaling for Multi-Turn Search Agents via Retrieval Grounding
Hyunho Kook, Junhyuk So, Tianyu Fu +2
Confidence-based voting aggregates parallel LLM rollouts by weighting each with internal signals such as token log probabilities, and has been actively studied for single-turn reas…
Stabilizing Direct Training of Spiking Neural Networks: Membrane Potential Initialization and Threshold-robust Surrogate Gradient
Hyunho Kook, Byeongho Yu, Jeong Min Oh +1
Recent advancements in the direct training of Spiking Neural Networks (SNNs) have demonstrated high-quality outputs even at early timesteps, paving the way for novel energy-efficie…
Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation
Junhyuk So, Hyunho Kook, Chaeyeon Jang +1
Autoregressive (AR) modeling has recently emerged as a promising new paradigm in visual generation, but its practical adoption is severely constrained by the slow inference speed o…
Grouped Speculative Decoding for Autoregressive Image Generation
Junhyuk So, Juncheol Shin, Hyunho Kook +1
Recently, autoregressive (AR) image models have demonstrated remarkable generative capabilities, positioning themselves as a compelling alternative to diffusion models. However, th…