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20242026
most citedLOTUS: A Leaderboard for Detailed Image Captioning from Quality to Societal Bias and User Preferences

1 citations · 2 across the 17 of their papers we have counts for

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cs.CL2026

EdgeWise: Bringing Long-Horizon Agents to the Edge via Selective Cloud Delegation

Zeru Shi, Jindong Jiang, Ryo Hachiuma +10

Complex and long-horizon agent tasks often rely on frontier models deployed in the cloud to achieve strong performance. However, using these models for every step of a long-horizon…

cs.AI2026

MLLMs Fail to Refuse when Using Tools Agentically

Rikiya Takehi, Ryo Hachiuma, Shaona Ghosh +3

Agentic multimodal large language models (MLLMs) have recently pushed the frontier of visual reasoning by calling tools such as zooming and tagging. Despite the recent strong succe…

cs.CL2026

Mid-Harness: Scaling Actions Between Model and Harness for Terminal Agents

Minki Kang, Ryo Hachiuma, Shaokun Zhang +8

Terminal agents act through stochastic model generations, yet the ability to generate a useful action does not ensure its reliable execution. A poor command (e.g., wrong package in…

cs.CV2026

Guardrail-Agnostic Societal Bias Evaluation in Large Vision-Language Models

Yusuke Hirota, Michael Ross Boone, Arun George Zachariah +4

We propose a societal bias evaluation method for large vision-language models (LVLMs) in the era of strong safety guardrails. Existing benchmarks rely on prompts that ask models to…

cs.CV2026

AnyGroundBench: A Multi-Domain Adaptation Benchmark for Video Grounding in VLMs

Rintaro Otsubo, Ryo Fujii, Reina Ishikawa +6

Vision-Language Models (VLMs) have shown strong performance in Spatio-Temporal Video Grounding (STVG), yet they are still evaluated mostly in a zero-shot manner on general-purpose…

cs.CV2026

SpatialClaw: Rethinking Action Interface for Agentic Spatial Reasoning

Seokju Cho, Ryo Hachiuma, Abhishek Badki +8

Spatial reasoning, the ability to determine where objects are, how they relate, and how they move in 3D, remains a fundamental challenge for vision-language models (VLMs). Tool-aug…

cs.CL2026

Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients

Byung-Kwan Lee, Ximing Lu, Shizhe Diao +8

Knowledge distillation transfers a teacher's competence to a small student but is brittle in the small-student regime: forcing the student to imitate logits from a much larger teac…

cs.CV2026

DVSM: Decoder-only View Synthesis Model Done Right

Cheng Sun, Jaesung Choe, Min-Hung Chen +2

Recent Large View Synthesis Models (LVSMs) advocate an encoder-decoder architecture that separates reconstruction and rendering into distinct networks. We re-examine this design. T…

cs.CL2026

Agent Explorative Policy Optimization for Multimodal Agentic Reasoning

Minki Kang, Shizhe Diao, Ryo Hachiuma +4

Vision-language models with extended reasoning succeed on complex problems, but many real-world problems require external tools that internal reasoning alone often cannot resolve.…

cs.SD2026

Speech-Hands: A Self-Reflection Voice Agentic Approach to Speech Recognition and Audio Reasoning with Omni Perception

Zhen Wan, Chao-Han Huck Yang, Jinchuan Tian +15

We introduce a voice-agentic framework that learns one critical omni-understanding skill: knowing when to trust itself versus when to consult external audio perception. Our work is…