5 papers
From RLVR to RLSVR: Task Transformation Induces Self-Verifiable Rewards for Open-Ended LLM Self-Improvement
Qinsi Wang, Jing Shi, Huazheng Wang +8
Reinforcement Learning with Verifiable Rewards (RLVR) has driven recent progress in reasoning-oriented large language models (LLMs) by enabling large-scale optimization. However, i…
CoT Referring: Improving Referring Expression Tasks with Grounded Reasoning
Qihua Dong, Luis Figueroa, Handong Zhao +5
Referring Expression Comprehension and Segmentation are critical tasks for assessing the integration of language understanding and image comprehension, serving as benchmarks for Mu…
More Than the Final Answer: Improving Visual Extraction and Logical Consistency in Vision-Language Models
Hoang Anh Just, Yifei Fan, Handong Zhao +6
Reinforcement learning from verifiable rewards (RLVR) has recently been extended from text-only LLMs to vision-language models (VLMs) to elicit long-chain multimodal reasoning. How…
SOHES: Self-supervised Open-world Hierarchical Entity Segmentation
Shengcao Cao, Jiuxiang Gu, Jason Kuen +7
Open-world entity segmentation, as an emerging computer vision task, aims at segmenting entities in images without being restricted by pre-defined classes, offering impressive gene…
GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration
Yue Fan, Handong Zhao, Ruiyi Zhang +3
Graphical User Interface (GUI) action grounding is a critical step in GUI automation that maps language instructions to actionable elements on GUI screens. Most recent works of GUI…