Geometric characterization of optimal classical RACs with explicit constructions, optimality proofs for several families, and a quantum RAC establishing classical-quantum separation for the (2^k-1, k) family.
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Single-layer two-head Transformers learn sparse XOR with O(polylog(d)) parameters in one gradient step, breaking the Omega(d) parameter bottleneck of FFNNs.
Introduces randomly infused advice (RIA) to analyze existing online algorithms with partial reliable advice infused into random bits, establishing improved competitive-ratio upper bounds (and often tight lower bounds) for paging, uniform metrical task systems, and online set cover as alpha increases
MooD introduces continuous valence-arousal modeling with VA-aware retrieval and perception-enhanced guidance for efficient, controllable affective image editing, plus a new AffectSet dataset.
Standard DFS and BFS suffice to recognize and certify trivially perfect graphs, split graphs, bipartite chain graphs, and proper interval graphs using pattern-avoiding vertex orderings.
SSL representation disentangles skill scheduling, structure, and logic using an LLM normalizer, improving skill discovery MRR@50 from 0.649 to 0.729 and risk assessment macro F1 from 0.409 to 0.509 over text baselines.
RDP-selected 13 layers for LoRA on Qwen3-8B-Base reach 81.67% on MMLU-Math, beating full 36-layer adaptation at 79.32% and random 13-layer selection at 75.56%.
Diffusion policies achieve 100% success on nominal mortise-tenon timber assembly and 75% average success under randomized 10 mm perturbations using force/torque sensing on an industrial robot.
citing papers explorer
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Random Access Codes: Explicit Constructions, Optimality, and Classical-Quantum Gaps
Geometric characterization of optimal classical RACs with explicit constructions, optimality proofs for several families, and a quantum RAC establishing classical-quantum separation for the (2^k-1, k) family.
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Transformers Provably Learn Sparse XOR with Polylogarithmic Parameters
Single-layer two-head Transformers learn sparse XOR with O(polylog(d)) parameters in one gradient step, breaking the Omega(d) parameter bottleneck of FFNNs.
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Online Algorithms with Randomly Infused Advice
Introduces randomly infused advice (RIA) to analyze existing online algorithms with partial reliable advice infused into random bits, establishing improved competitive-ratio upper bounds (and often tight lower bounds) for paging, uniform metrical task systems, and online set cover as alpha increases
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MooD: Perception-Enhanced Efficient Affective Image Editing via Continuous Valence-Arousal Modeling
MooD introduces continuous valence-arousal modeling with VA-aware retrieval and perception-enhanced guidance for efficient, controllable affective image editing, plus a new AffectSet dataset.
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On the power of standard DFS and BFS
Standard DFS and BFS suffice to recognize and certify trivially perfect graphs, split graphs, bipartite chain graphs, and proper interval graphs using pattern-avoiding vertex orderings.
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From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills
SSL representation disentangles skill scheduling, structure, and logic using an LLM normalizer, improving skill discovery MRR@50 from 0.649 to 0.729 and risk assessment macro F1 from 0.409 to 0.509 over text baselines.
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RDP LoRA: Geometry-Driven Identification for Parameter-Efficient Adaptation in Large Language Models
RDP-selected 13 layers for LoRA on Qwen3-8B-Base reach 81.67% on MMLU-Math, beating full 36-layer adaptation at 79.32% and random 13-layer selection at 75.56%.
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Contact-Rich Robotic Assembly in Construction via Diffusion Policy Learning
Diffusion policies achieve 100% success on nominal mortise-tenon timber assembly and 75% average success under randomized 10 mm perturbations using force/torque sensing on an industrial robot.