Tootfinder

Self-Reflective Generation at Test Time
Jian Mu, Qixin Zhang, Zhiyong Wang, Menglin Yang, Shuang Qiu, Chengwei Qin, Zhongxiang Dai, Yao Shu
https://arxiv.org/abs/2510.02919 http…

Self-Reflective Generation at Test Time
Large language models (LLMs) increasingly solve complex reasoning tasks via long chain-of-thought, but their forward-only autoregressive generation process is fragile; early token errors can cascade, which creates a clear need for self-reflection mechanisms. However, existing self-reflection either performs revisions over full drafts or learns self-correction via expensive training, both fundamentally reactive and inefficient. To address this, we propose Self-Reflective Generation at Test Time …

AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving
Zhenlong Yuan, Jing Tang, Jinguo Luo, Rui Chen, Chengxuan Qian, Lei Sun, Xiangxiang Chu, Yujun Cai, Dapeng Zhang, Shuo Li
https://arxiv.org/abs/2509.01944

AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving
Vision-Language-Action (VLA) models in autonomous driving systems have recently demonstrated transformative potential by integrating multimodal perception with decision-making capabilities. However, the interpretability and coherence of the decision process and the plausibility of action sequences remain largely underexplored. To address these issues, we propose AutoDrive-R$^2$, a novel VLA framework that enhances both reasoning and self-reflection capabilities of autonomous driving systems thr…

Raiders' Surprising Self-Reflection Uncovers Fascinating Truths https://www.si.com/nfl/raiders/las-vegas-pete-carroll-indianpolis-colts-brock-bowers-ashton-jeanty

Discovering Self-Regulated Learning Patterns in Chatbot-Powered Education Environment
Yilin Lyu, Ren Ding
https://arxiv.org/abs/2510.01275 https://arxiv.or…

Discovering Self-Regulated Learning Patterns in Chatbot-Powered Education Environment
The increasing adoption of generative AI (GenAI) tools such as chatbots in education presents new opportunities to support students' self-regulated learning (SRL), but also raises concerns about how learners actually engage in planning, executing, and reflection when learning with a chatbot. While SRL is typically conceptualized as a sequential process, little is known about how it unfolds during real-world student-chatbot interactions. To explore this, we proposed Gen-SRL, an annotation schema…

Strong Feller Regularisation of 1-d Nonlinear Transport by Reflected Ornstein-Uhlenbeck Noise
Max-K. von Renesse, Alexander Wei{\ss}
https://arxiv.org/abs/2508.01355 https://

Strong Feller Regularisation of 1-d Nonlinear Transport by Reflected Ornstein-Uhlenbeck Noise
We consider equations of nonlinear transport on the circle with regular self interactions appearing in aggregation models and deterministic mean field dynamics. We introduce a random perturbation of such systems through a stochastic orientation preserving flow, which is given as an integrated infinite dimensional periodic Ornstein- Uhlenbeck process with reflection. As our main result we show that the induced stochastic dynamics yields a measure valued Markov process on a class of regular measu…

"Having Lunch Now": Understanding How Users Engage with a Proactive Agent for Daily Planning and Self-Reflection
Adnan Abbas, Caleb Wohn, Arnav Jagtap, Eugenia H Rho, Sang Won Lee
https://arxiv.org/abs/2509.24073

"Having Lunch Now": Understanding How Users Engage with a Proactive Agent for Daily Planning and Self-Reflection
Conversational agents have been studied as tools to scaffold planning and self-reflection for productivity and well-being. While prior work has demonstrated positive outcomes, we still lack a clear understanding of what drives these results and how users behave and communicate with agents that act as coaches rather than assistants. Such understanding is critical for designing interactions in which agents foster meaningful behavioral change. We conducted a 14-day longitudinal study with 12 parti…

Calibrated Reasoning: An Explanatory Verifier for Dynamic and Efficient Problem-Solving
Anisha Garg, Engin Tekin, Yash More, David Bick, Nishit Neema, Ganesh Venkatesh
https://arxiv.org/abs/2509.19681 …

Calibrated Reasoning: An Explanatory Verifier for Dynamic and Efficient Problem-Solving
Advanced test-time computing strategies are essential for scaling reasoning models, but their effectiveness is capped by the models' poor self-evaluation. We propose a pairwise Explanatory Verifier, trained via reinforcement learning (GRPO), that produces calibrated confidence scores and associated natural language reasoning for generated solutions. Our verifier improves the accuracy and efficiency of test-time strategies like best-of-n and self-reflection. Crucially, it excels at identifying c…

Agentic Workflow for Education: Concepts and Applications
Yuan-Hao Jiang, Yijie Lu, Ling Dai, Jiatong Wang, Ruijia Li, Bo Jiang
https://arxiv.org/abs/2509.01517 https://

Agentic Workflow for Education: Concepts and Applications
With the rapid advancement of Large Language Models (LLMs) and Artificial Intelligence (AI) agents, agentic workflows are showing transformative potential in education. This study introduces the Agentic Workflow for Education (AWE), a four-component model comprising self-reflection, tool invocation, task planning, and multi-agent collaboration. We distinguish AWE from traditional LLM-based linear interactions and propose a theoretical framework grounded in the von Neumann Multi-Agent System (MA…

Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse
Akriti Verma, Shama Islam, Valeh Moghaddam, Adnan Anwar
https://arxiv.org/abs/2509.00696 htt…

Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse
The pervasiveness of online toxicity, including hate speech and trolling, disrupts digital interactions and online well-being. Previous research has mainly focused on post-hoc moderation, overlooking the real-time emotional dynamics of online conversations and the impact of users' emotions on others. This paper presents a graph-based framework to identify the need for emotion regulation within online conversations. This framework promotes self-reflection to manage emotional responses and encour…

FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models
Yufan Song, Jiatao Zhang, Zeng Gu, Qingmiao Liang, Tuocheng Hu, Wei Song, Shiqiang Zhu
https://arxiv.org/abs/2507.14975

FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models
Autonomous error correction is critical for domestic robots to achieve reliable execution of complex long-horizon tasks. Prior work has explored self-reflection in Large Language Models (LLMs) for task planning error correction; however, existing methods are constrained by inflexible self-reflection mechanisms that limit their effectiveness. Motivated by these limitations and inspired by human cognitive adaptation, we propose the Flexible Constructivism Reflection Framework (FCRF), a novel Ment…

Happiness Break: A Meditation on the Uniqueness of Your Voice https://greatergood.berkeley.edu/podcasts/item/happiness_break_a_meditation_on_t…

Happiness Break: A Meditation on the Uniqueness of Your Voice
Embrace the beauty of your accent in this self-compassion meditation that guides you in a reflection of your history, heritage, and connection to your ancestors.

"In my defense, only three hours on Instagram": Designing Toward Digital Self-Awareness and Wellbeing
Karthik S. Bhat, Jiayue Melissa Shi, Wenxuan Song, Dong Whi Yoo, Koustuv Saha
https://arxiv.org/abs/2509.21860

"In my defense, only three hours on Instagram": Designing Toward Digital Self-Awareness and Wellbeing
Screen use pervades daily life, shaping work, leisure, and social connections while raising concerns for digital wellbeing. Yet, reducing screen time alone risks oversimplifying technology's role and neglecting its potential for meaningful engagement. We posit self-awareness -- reflecting on one's digital behavior -- as a critical pathway to digital wellbeing. We developed WellScreen, a lightweight probe that scaffolds daily reflection by asking people to estimate and report smartphone use. In …

Injecting External Knowledge into the Reasoning Process Enhances Retrieval-Augmented Generation
Minghao Tang, Shiyu Ni, Jiafeng Guo, Keping Bi
https://arxiv.org/abs/2507.19333 h…

Injecting External Knowledge into the Reasoning Process Enhances Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) has been widely adopted to augment large language models (LLMs) with external knowledge for knowledge-intensive tasks. However, its effectiveness is often undermined by the presence of noisy (i.e., low-quality) retrieved passages. Enhancing LLMs' robustness to such noise is critical for improving the reliability of RAG systems. Recent advances have equipped LLMs with strong reasoning and self-reflection capabilities, allowing them to identify and correct err…

Calibrated Reasoning: An Explanatory Verifier for Dynamic and Efficient Problem-Solving
Anisha Garg, Engin Tekin, Yash More, David Bick, Nishit Neema, Ganesh Venkatesh
https://arxiv.org/abs/2509.19681 …

Calibrated Reasoning: An Explanatory Verifier for Dynamic and Efficient Problem-Solving
Advanced test-time computing strategies are essential for scaling reasoning models, but their effectiveness is capped by the models' poor self-evaluation. We propose a pairwise Explanatory Verifier, trained via reinforcement learning (GRPO), that produces calibrated confidence scores and associated natural language reasoning for generated solutions. Our verifier improves the accuracy and efficiency of test-time strategies like best-of-n and self-reflection. Crucially, it excels at identifying c…

intentional self portraits
#photography #begonia

Tao-Technology for Teen Mobile Use: Harmonizing Adaptation, Autonomy, and Reflection
Pengyu Zhu, Janghee Cho
https://arxiv.org/abs/2507.12204 https://

Tao-Technology for Teen Mobile Use: Harmonizing Adaptation, Autonomy, and Reflection
Adolescents' mobile technology use is often regulated through rigid control mechanisms that fail to account for their autonomy and natural usage patterns. Drawing on Taoist philosophy, particularly Wu Wei, Yin-Yang, and Zi Ran, this position paper proposes Tao-Technology, a self-organizing, adaptive regulatory framework. Integrating insights from Reflective Informatics and Information Ecologies, we explore how mobile technology can dynamically adjust to context while fostering self-reflection a…

A Geometrically Consistent Matching Framework for Side-Scan Sonar Mapping
Can Lei, Hayat Rajani, Nuno Gracias, Rafael Garcia, Huigang Wang
https://arxiv.org/abs/2509.11255 https…

A Geometrically Consistent Matching Framework for Side-Scan Sonar Mapping
Robust matching of side scan sonar imagery remains a fundamental challenge in seafloor mapping due to view dependent backscatter, shadows, and geometric distortion. This paper proposes a novel matching framework that combines physical decoupling and geometric consistency to enhance correspondence accuracy and consistency across viewpoints. A self supervised multi branch network, derived from the Lambertian reflection model, decomposes raw sonar images into seabed reflectivity, terrain elevation…

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Akriti Verma, Shama Islam, Valeh Moghaddam, Adnan Anwar
https://arxiv.org/abs/2507.11477

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Online conversations are often interrupted by trolling, which causes emotional distress and conflict among users. Previous research has focused on moderating harmful content after it has been posted, but ways to manage emotions in real-time remain unexplored. This study suggests a comment queuing mechanism that delays comment publishing, encourages self-reflection, and reduces the impact of impulsive and toxic comments. To assess the efficacy of this approach, a mixed-method research design is …

ClearFairy: Capturing Creative Workflows through Decision Structuring, In-Situ Questioning, and Rationale Inference
Kihoon Son, DaEun Choi, Tae Soo Kim, Young-Ho Kim, Sangdoo Yun, Juho Kim
https://arxiv.org/abs/2509.14537

ClearFairy: Capturing Creative Workflows through Decision Structuring, In-Situ Questioning, and Rationale Inference
Capturing professionals' decision-making in creative workflows is essential for reflection, collaboration, and knowledge sharing, yet existing methods often leave rationales incomplete and implicit decisions hidden. To address this, we present CLEAR framework that structures reasoning into cognitive decision steps-linked units of actions, artifacts, and self-explanations that make decisions traceable. Building on this framework, we introduce ClearFairy, a think-aloud AI assistant for UI design …