16 citations · 22 across the 12 of their papers we have counts for
12 papers
LongWoF-Bench: Evaluating EvoMap Genes for Verifiable Long-Workflow Tasks
Xiao Zhang, Qumeng Sun, Jiahao Li +5
Large language models are increasingly expected to execute complex workflows whose success depends on maintaining interdependent constraints and producing artifacts that satisfy st…
AutoResearch: Insight In, Hallucination Out
Yiming Ren, Xiang Liu, Bruno +5
Autonomous research systems are increasingly capable of executing long research workflows, yet automation alone does not ensure that the resulting process remains scientifically gr…
From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution
Junjie Wang, Yiming Ren, Haoyang Zhang
This beta technical report asks how reusable experience should be represented so that it can function as effective test-time control and as a substrate for iterative evolution. We…
Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO
Yiran Xu, Yiming Ren, Zicheng Lin +8
We identify a new dimension for enhancing rollout diversity in Group Relative Policy Optimization (GRPO) for LLMs. While GRPO relies on diverse rollouts, prevailing strategies prim…
Mitigating the Reasoning Tax in Vision-Language Fine-Tuning with Input-Adaptive Depth Aggregation
Yiming Ren, Yujiu Yang, Junjie Wang
Supervised fine-tuning (SFT) on visual instruction data often improves perceptual capabilities in vision-language models (VLMs) while degrading reasoning performance, creating a pe…
SIN-Bench: Tracing Native Evidence Chains in Long-Context Multimodal Scientific Interleaved Literature
Yiming Ren, Junjie Wang, Yuxin Meng +11
Evaluating whether multimodal large language models truly understand long-form scientific papers remains challenging: answer-only metrics and synthetic "Needle-In-A-Haystack" tests…
AnyCap Project: A Unified Framework, Dataset, and Benchmark for Controllable Omni-modal Captioning
Yiming Ren, Zhiqiang Lin, Yu Li +8
Controllable captioning is essential for precise multimodal alignment and instruction following, yet existing models often lack fine-grained control and reliable evaluation protoco…
Multimodal Fusion for Sim2real Transfer in Visual Reinforcement Learning
Zichun Xu, Jingdong Zhao, Chenyu Guo +6
Depth information is robust to scene appearance variations and inherently carries 3D spatial details. Thus, a visual backbone based on the vision transformer is proposed to fuse RG…
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Zhe Chen, Weiyun Wang, Yue Cao +39
We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing signif…
Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance
Zhangwei Gao, Zhe Chen, Erfei Cui +12
Multimodal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a broad spectrum of domains. However, the large model scale and as…
Needle In A Multimodal Haystack
Weiyun Wang, Shuibo Zhang, Yiming Ren +13
With the rapid advancement of multimodal large language models (MLLMs), their evaluation has become increasingly comprehensive. However, understanding long multimodal content, as a…
The All-Seeing Project V2: Towards General Relation Comprehension of the Open World
Weiyun Wang, Yiming Ren, Haowen Luo +9
We present the All-Seeing Project V2: a new model and dataset designed for understanding object relations in images. Specifically, we propose the All-Seeing Model V2 (ASMv2) that i…