cs papers | Gist.Science

Kinodynamic Motion Retargeting for Humanoid Locomotion via Multi-Contact Whole-Body Trajectory Optimization

This paper introduces KDMR, a novel framework that formulates humanoid motion retargeting as a multi-contact whole-body trajectory optimization problem incorporating rigid-body dynamics and ground reaction forces to generate physically consistent, dynamically feasible locomotion trajectories that significantly outperform purely kinematic methods in both motion quality and downstream control policy performance.

Xiaoyu Zhang, Steven Haener, Varun Madabushi, Maegan TuckerWed, 11 Ma💻 cs

Tetris is Hard with Just One Piece Type

This paper establishes that Tetris clearing and survival are NP-hard for any single tetromino type except the O-piece under the Super Rotation System, disproving a long-standing conjecture about the I-piece, while simultaneously providing polynomial-time algorithms for cases involving only dominoes or $1\times k$ pieces under specific initial board conditions.

MIT Hardness Group, Josh Brunner, Erik D. Demaine, Della Hendrickson, Jeffery LiWed, 11 Ma💻 cs

ReCoSplat: Autoregressive Feed-Forward Gaussian Splatting Using Render-and-Compare

ReCoSplat is an autoregressive feed-forward Gaussian Splatting model that overcomes the training-inference pose mismatch dilemma through a novel Render-and-Compare module and achieves state-of-the-art online novel view synthesis with efficient long-sequence handling via hybrid KV cache compression.

Freeman Cheng, Botao Ye, Xueting Li, Junqi You, Fangneng Zhan, Ming-Hsuan YangWed, 11 Ma💻 cs

TiPToP: A Modular Open-Vocabulary Planning System for Robotic Manipulation

TiPToP is a modular, open-vocabulary robotic planning system that integrates pretrained vision foundation models with a Task and Motion Planner to solve multi-step manipulation tasks from RGB images and natural language instructions without requiring any robot-specific training data, achieving performance comparable to or better than fine-tuned vision-language-action models while enabling detailed failure mode analysis.

William Shen, Nishanth Kumar, Sahit Chintalapudi, Jie Wang, Christopher Watson, Edward Hu, Jing Cao, Dinesh Jayaraman, Leslie Pack Kaelbling, Tomás Lozano-PérezWed, 11 Ma💻 cs

d-DNNF Modulo Theories: A General Framework for Polytime SMT Queries

This paper introduces a general framework that extends Knowledge Compilation to Satisfiability Modulo Theories (SMT) by combining input formulas with pre-computed theory lemmas to enable polytime propositional-style querying of compiled SMT d-DNNFs.

Gabriele Masina, Emanuale Civini, Massimo Michelutti, Giuseppe Spallitta, Roberto SebastianiWed, 11 Ma💻 cs

Learning from Viral Content

This paper employs an equilibrium model to demonstrate that while news feed algorithms prioritizing viral stories can enhance information aggregation, they also risk creating self-perpetuating steady states where rational users collectively share and reinforce incorrect information, highlighting critical implications for platform design.

Krishna Dasaratha, Kevin HeTue, 10 Ma💻 cs

A Robust Multi-Item Auction Design with Statistical Learning

This paper proposes a novel statistical learning framework for multi-item auctions that utilizes nonparametric density estimation and credible intervals to implement two cost-reducing strategies, which maintain key economic properties like incentive compatibility and fairness while outperforming alternative methods in both revenue maximization and implementation efficiency.

Jiale Han, Xiaowu DaiTue, 10 Ma💻 cs

Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation

This paper proposes a mutual conditional blended-target domain adaptation framework that aligns categorical distributions and rectifies classifier bias through uncertainty-guided discrimination and low-level feature augmentation, achieving state-of-the-art performance even without explicit domain labels and under label distribution shifts.

Pengcheng Xu, Boyu Wang, Charles LingTue, 10 Ma💻 cs

Critical Relaxed-Stable Matchings with Ties in the Many-to-Many Setting

This paper investigates the many-to-many bipartite matching problem with ties and lower quotas, proving that while a maximum-size critical relaxed-stable matching is NP-hard to compute, a $\frac{2}{3}$ -approximation can be achieved in polynomial time.

Meghana Nasre, Prajakta Nimbhorkar, Keshav RanjanTue, 10 Ma💻 cs

Utility Theory based Cognitive Modeling in the Application of Robotics: A Survey

This survey reviews the application of utility theory to cognitive modeling in robotics, tracing its evolution from behavior-based approaches to value systems that guide decision-making, learning, and cooperation in single and multi-agent environments, while identifying current limitations and proposing future research directions.

Qin YangTue, 10 Ma💻 cs

Toward 6G Sidelink Reliability: MAC PRR Modeling for NR Mode 2 SPS and ns-3 Validation

This paper presents an analytical MAC-layer model for 5G NR Sidelink Mode 2 that explicitly incorporates standardized Semi-Persistent Scheduling features to derive closed-form expressions for packet reception ratio, which are validated against ns-3 simulations to provide design insights for enhancing 6G sidelink reliability.

Liu Cao, Zhaoyu Liu, Lyutianyang ZhangTue, 10 Ma💻 cs

Online Dispatching and Routing for Automated Guided Vehicles in Pickup and Delivery Systems on Loop-Based Graphs

This paper proposes and validates a loop-based algorithm for the online, conflict-free scheduling and routing of automated guided vehicles in pickup and delivery systems, demonstrating its superior or comparable performance to exact, greedy, and metaheuristic methods in terms of solution quality and computational efficiency.

Louis Stubbe, Jens Goemaere, Jan GoedgebeurTue, 10 Ma💻 cs

Multi-Scale Distillation for RGB-D Anomaly Detection on the PD-REAL Dataset

This paper introduces PD-REAL, a novel large-scale RGB-D dataset for unsupervised anomaly detection based on Play-Doh models, and proposes a multi-scale teacher-student framework with hierarchical distillation that leverages 3D information to achieve superior detection accuracy compared to existing methods.

Jianjian Qin, Chao Zhang, Chunzhi Gu, Zi Wang, Jun Yu, Yijin Wei, Hui Xiao, Xin YuaTue, 10 Ma💻 cs

Joint User Association and Resource Allocation for Adaptive Semantic Communication in 5G and Beyond Networks

This paper proposes a joint user association and resource allocation framework for Adaptive Semantic Communication in 5G and beyond networks, which dynamically adjusts DNN-based transceivers to address user heterogeneity and maximizes system utility under energy and latency constraints through a decomposed, polynomial-time algorithm.

Xingqiu He, Chaoqun You, Zihan Chen, Yao Sun, Dongzhu Liu, Tony Q. S. Quek, Yue GaoTue, 10 Ma💻 cs

Challenges in Restructuring Community-based Moderation

Through an analysis of Wikipedia's Flagged Revisions initiative, this paper identifies how restructuring community-based moderation is hindered by conflicts between new systems and existing social norms, as well as the complex costs and assessment difficulties arising from the intricate relationship between platforms and self-governed communities.

Chau Tran, Kejsi Take, Kaylea Champion, Benjamin Mako Hill, Rachel GreenstadtTue, 10 Ma💻 cs

Deepfake Generation and Detection: A Benchmark and Survey

This paper presents a comprehensive survey and benchmark of deepfake generation and detection, unifying task definitions, reviewing state-of-the-art methods across four key generation fields and forgery detection, and analyzing current challenges and future research directions.

Gan Pei, Jiangning Zhang, Menghan Hu, Zhenyu Zhang, Chengjie Wang, Yunsheng Wu, Guangtao Zhai, Jian Yang, Dacheng TaoTue, 10 Ma💻 cs

Goldilocks Test Sets for Face Verification

This paper proposes three high-quality, controlled test sets (Hadrian, Eclipse, and ND-Twins) designed to challenge face verification models on natural variations in facial attributes and similar-looking identities, while introducing "Goldilocks" rules to ensure balanced difficulty and demographic fairness without artificially degrading image quality.

Haiyu Wu, Sicong Tian, Aman Bhatta, Jacob Gutierrez, Grace Bezold, Genesis Argueta, Karl Ricanek Jr., Michael C. King, Kevin W. BowyerTue, 10 Ma💻 cs

RDM: Recurrent Diffusion Model for Human Motion Generation

This paper proposes RDM, a recurrent diffusion model that leverages Normalizing Flows to condition generation on preceding noisy frames, enabling efficient, long-duration human motion synthesis with reduced computational costs while maintaining high alignment with text prompts.

Mirgahney Mohamed, Harry Jake Cunningham, Marc P. Deisenroth, Lourdes AgapitoTue, 10 Ma💻 cs

Influence-Based Reward Modulation for Implicit Communication in Human-Robot Interaction

This paper proposes a method to foster implicit communication in human-robot interaction by modulating inter-agent influence through Transfer Entropy within a reward framework, demonstrating that enhancing influence improves collaboration while resisting it promotes independence, as validated through simulations and real-world experiments.

Haoyang Jiang, Elizabeth A. Croft, Michael G. BurkeTue, 10 Ma💻 cs

MORCoRA: Multi-Objective Refactoring Recommendation Considering Review Availability

This paper proposes MORCoRA, a multi-objective search-based technique that recommends code quality-improving refactoring sequences along with suitable reviewers by simultaneously optimizing for expertise and workload availability to ensure the refactorings can be promptly reviewed.

Lei Chen, Shinpei HayashiTue, 10 Ma💻 cs

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