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researcher

Song Han

19 papers hereh-index 132.3k citations22 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author15
  • last author3

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV15
  • cs.LG2
  • cs.AI1
  • cs.RO1
same name
  • Song Han — 52 papers, h 55
  • Song Han — 37 papers, h 15
  • Song Han — 17 papers, h 16
  • Song Han — 12 papers, h 10
  • Song Han — 12 papers, h 8
  • Song Han — 7 papers, h 19

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedVILA: On Pre-training for Visual Language Models

6 citations · 13 across the 18 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

Parason: Revealing Subtask and Trial Parallelism in LLM Reasoning

Zhengyang Zhang, Zijian Zhang, Jiaxuan Gao +4

Scaling test-time reasoning has substantially improved the problem-solving ability of large language models (LLMs), but standard autoregressive decoding still executes long reasoni…

cs.CV2026

Reinforcing Dual-Path Reasoning in Spatial Vision Language Models

Yatai Ji, An-Chieh Cheng, Yang Fu +13

Spatial VLMs have made substantial progress in geometric perception, yet complex spatial reasoning requiring multi-step inference over depth, distance, and scene relations remains…

cs.CV2026

Grounded 3D-Aware Spatial Vision-Language Modeling

An-Chieh Cheng, Yang Fu, Yatai Ji +12

We present GR3D, a spatial vision language model equipped with three complementary grounding capabilities--explicit 2D grounding, implicit 2D grounding, and monocular 3D grounding-…

cs.CV2026

EGM: Efficient Visual Grounding Language Models

Guanqi Zhan, Changye Li, Zhijian Liu +4

Visual grounding is an essential capability of Visual Language Models (VLMs) to understand the real physical world. Previous state-of-the-art grounding visual language models usual…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.