Preprint2025
Sharp: Steering hallucination in lvlms via representation engineering
Unknown
SHARP is a representation-level intervention framework that modulates hallucination in LVLMs by steering internal representations.
0Jan 1, 2025
AI Research
AI & ML Research Papers
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26 papersPreprint2026
Unlocking multilingual reasoning capability of llms and lvlms through representation engineering
Unknown
Proposes MRRE, a training-free inference-time method using representation engineering to enhance multilingual reasoning in LLMs and LVLMs without additional training data.
0Jan 1, 2026Reasoning
Preprint2025
Can World Models Benefit VLMs for World Dynamics?
Unknown
This paper explores how generative world models can provide priors to vision-language models (VLMs) for improved understanding of world dynamics in common vision tasks.
0Oct 1, 2025Computer Vision
arXiv
Preprint2025
Fastvlm: Efficient vision encoding for vision language models
Unknown
FastVLM introduces an efficient vision encoding method that reduces computational cost while maintaining high performance in text-rich image understanding tasks.
0Jan 1, 2025Scaling LawsComputer Vision
Preprint2023
Lvlm-ehub: A comprehensive evaluation benchmark for large vision-language models
Unknown
This paper introduces LVLM-eHub, a comprehensive evaluation benchmark for Large Vision-Language Models, systematically assessing their capabilities across diverse multimodal tasks.
0Jun 1, 2023BenchmarksComputer Vision
arXiv
Preprint2024
Effectiveness assessment of recent large vision-language models
Unknown
This paper assesses the effectiveness of recent large vision-language models (LVLMs) in achieving artificial general intelligence, focusing on their performance across various tasks.
0Jan 1, 2024Computer Vision
Preprint2026
Planner Matters! An Efficient and Unbalanced Multi-agent Collaboration Framework for Long-horizon Planning
Unknown
This paper proposes an efficient and unbalanced multi-agent collaboration framework for long-horizon planning, using a final-outcome-based reward and a VLM evaluator to provide stable feedback.
0May 1, 2026
arXiv
Preprint2026
Spatially Grounded Long-Horizon Task Planning in the Wild
Unknown
This paper evaluates closed- and open-source VLMs as planners, showing that spatially grounded long-horizon planning remains a major unsolved challenge.
0Mar 1, 2026
arXiv
Preprint2026
SpatialCLI: Learning to Reason With Spatial Tools, Then Without Them
Yang Zhou, Zixuan Huang, Sunzhu Li, et al.
SpatialCLI teaches VLMs to reason with spatial tools and progressively internalize specialist perceptual capabilities, raising Qwen3-VL-8B-Instruct from 29.3% to 84.6% on MindCube.
0Jul 30, 2026ReasoningBenchmarks
arXiv
Preprint2026
UltraViT: Latency-Optimized On-device Vision Encoder for Large Vision-Language Models
Ioannis Maniadis Metaxas, Adrian Bulat, Alberto Baldrati, et al.
UltraViT is a latency-optimized vision encoder for LVLMs using a pyramidal architecture with heterogeneous spatial mixers and a two-stage generative pre-training strategy, achieving 1.7x speedup on-device.
0Jul 25, 2026MultimodalAlignment
arXiv
PreprintarXiv.org2025
Multi-Agent Collaboration for Multimodal LLMs
James Y. Huang, Sheng Zhang, Qianchu Liu, et al.
Proposes BeMyEyes, a multi-agent framework that uses a small VLM as a perceiver and a text-only LLM as a reasoner to achieve multimodal reasoning without training large-scale models.
6Nov 24, 2025Large Language ModelsFine Tuning
arXiv
Preprint2026
SceneActBench: Can Agents Act on the 3D Scenes They See?
Yifei Zhao, Xiangxin Zhou, Wenhao Yang, et al.
SceneActBench benchmarks VLM agents on acting in multi-object 3D scenes via a unified agent-environment loop, revealing no model performs consistently across five tasks.
0Jul 24, 2026BenchmarksComputer Vision
arXiv