Box Maze: A Process-Control Architecture for Reliable LLM Reasoning
Box Maze framework reduces LLM reasoning error rate to below 1% through memory grounding, structured inference, and boundary enforcement.
Zou Qiang
Box Maze framework reduces LLM reasoning error rate to below 1% through memory grounding, structured inference, and boundary enforcement.
Zou Qiang
ADMM-based distributed MPC with control barrier functions for quadrupedal robots reduces planning time by 51%.
Yicheng Zeng, Ruturaj S. Sambhus, Basit Muhammad Imran et al.
ARIADNE uses DPO and RL for coronary angiography, achieving a centerline Dice of 0.838.
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MAPG uses multi-agent probabilistic grounding for metric-semantic goal localization in vision-language navigation, excelling on the HM-EQA benchmark.
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PPI estimator is algebraically equivalent to Cassel et al.'s difference estimator, combining ML predictions with few labels for statistical inference.
Reagan Mozer
VEPO enhances translation quality and tokenization efficiency for low-resource languages using reinforcement learning with verifiable rewards.
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Construct Karhunen-Loève expansions using Fredholm integral equation, combined with SVD for consistent solutions.
Cosmin Safta, Habib N. Najm
Fast interpretable autoregressive estimation using neural network backpropagation, achieving 12.6x speedup.
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OmniAnomaly and PCA perform comparably on the SMD dataset, especially without point adjustment.
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The paper introduces a maximum-entropy exploration method using future state-action visitation measures, improving feature visitation and convergence speed.
Adrien Bolland, Gaspard Lambrechts, Damien Ernst
Using BERT Score and expert evaluation, this study analyzes ChatGPT-4o, GeminiAI, and Perplexity AI's performance in generating Telugu maternal health responses, with Gemini leading.
Anagani Bhanusree, Sai Divya Vissamsetty, K VenkataKrishna Rao et al.
Proposes a reference-free simulation framework by training independent user and recommender simulators for more realistic dialogues.
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Recover sparse neural connectivity from partial measurements using a covariance-based method with Granger-causality refinement.
Quilee Simeon
ChoiceEval framework reveals geographic bias in LLM brand and cultural preferences, notably favoring US entities.
Jasmine Rienecker, Katarina Mpofu, Naman Goel et al.
ALIGN uses adversarial learning to enhance cross-session generalization in speech neuroprostheses, significantly reducing phoneme and word error rates.
Zhanqi Zhang, Shun Li, Bernardo L. Sabatini et al.
The cHM algorithm is a universal framework for continuous optimization, excelling on 28 benchmark functions.
Piotr A. Kowalski, Szymon Kucharczyk, Jacek Mańdziuk
Introduced Spatio-Temporal Token Scoring (STTS) to enhance video VLMs efficiency by 62% with minimal performance drop.
Jianrui Zhang, Yue Yang, Rohun Tripathi et al.
Loc3R-VLM enables language-based localization and 3D reasoning from monocular video input, outperforming existing methods.
Kevin Qu, Haozhe Qi, Mihai Dusmanu et al.
LoST efficiently tokenizes 3D shapes by semantic salience for autoregressive generation, using only 0.1%-10% of tokens.
Niladri Shekhar Dutt, Zifan Shi, Paul Guerrero et al.
Efficient training-free multi-token prediction via embedding-space probing, improving LLaMA3 acceptance length by 12%.
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