k-REWB matching cannot be solved in O(n to the 2k minus epsilon) time under SETH, is W[2]-hard parameterized by expression length, and 2-use 2-REWBs require superlinear time unless triangle detection does; 1-use REWBs admit an O(n log squared n) algorithm.
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The Theory of Industrial Organization
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Deciding DFA primality is NP-hard, established by reduction from propositional satisfiability using a characterization of primality for a relevant class of automata.
Introduces PIN priority queue and neighbor-aware tree operations claiming 32 million order messages per second on one CPU core for trading matching engines.
Assuming exponential-family distributions for variational posteriors and priors extends the free-energy principle–predictive coding correspondence to exhibit biological neural properties such as nonlinearity, heterogeneity, and positive firing rates, with training via local plasticity rules.
CyberEvolver introduces a four-layer self-evolving agent architecture with trace-to-diagnosis and population beam search that raises seed agent success rates by 13.6% on CTF, exploitation, and penetration tasks across four LLMs.
Local attention in fixed-precision transformers introduces a second past operator in linear temporal logic, strictly increasing expressivity over global attention alone, with hybrids being most expressive.
TouchPort collapses the multi-stage process of discovering, consenting to, and syncing mixed reality encounters into one embodied handshake-and-pull gesture.
Local retail concentration increased almost as much as national concentration from 1992 to 2012, mainly from multi-market firm expansion, and accounts for one-quarter to one-third of the rise in retail gross margins.
FLaG is a frequency-domain module using FFT, latent queries, and gating that improves token aggregation and shows gains on ESM2 AMP prediction and CIFAR-100 image classification while staying competitive on text tasks.
Agentic Redux claims provably correct LLM agent executions on suitable domains via typed lambda calculus with full decision logging, demonstrated on healthcare compliance and security disclosure with supporting code.
TRACER combines a controller-regret layer using regret matching for speak/skip decisions with a generation-credit layer using GSPO rewards to enable learned collaboration in multi-LLM reasoning.
EnactToM is an evolving benchmark of embodied multi-agent tasks that tests functional Theory of Mind by requiring agents to act optimally on implicit beliefs in partially observable 3D environments.
The study proposes the Gradual Voluntary Participation (GVP) framework to reconceptualize participatory AI governance in journalism as a gradual and voluntary process using a bidimensional matrix.
SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.
Raven automates Scratch program assessment by having instructors specify task-level video generation rules and using LLMs to analyze resulting videos for behavioral compliance, outperforming prior tools on real student submissions.
The authors instantiate a generalized-Fano framework using squared Hellinger distance to derive explicit Bayesian CVaR lower bounds for interactive decision problems including Gaussian bandits.
Checksum Count Vectors enable robust similarity search to identify duplicate and variant legacy media recordings with high accuracy despite substantial data damage.
Hierarchy-informed curricular optimization of heterogeneous whole-brain models enables generalization to new subjects and prediction of behavioral abilities from parameters.
Bayesian joint estimation of Hurst parameter and volatility in fractional SDE models is developed to propagate parameter uncertainty into fractional Black-Scholes option prices.
The Stakeholder Grounding Exercise shows neural text embeddings are 19-26pp less reliable than human experts at capturing semantic distinctions, with misalignment strongly correlated to poorer clustering performance (ρ=0.9), replicated across Danish policy and US AI domains.
CTEM framework links behavioral history to evolving emotional states with user feedback updates, instantiated as Auri agent and tested in a 21-day study showing gains in naturalness, coherence, and emotional harmony.
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
Software practitioners are unaligning from technocapitalism through mockery, Luddism, labor organizing, and interest in anarchism and communism.
A quantum-inspired global search method called QIEO outperforms traditional solvers in recovering sparse structures and robust fitting by maintaining a broad view of possible solutions.
citing papers explorer
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On the Complexity of the Matching Problem of Regular Expressions with Backreferences
k-REWB matching cannot be solved in O(n to the 2k minus epsilon) time under SETH, is W[2]-hard parameterized by expression length, and 2-use 2-REWBs require superlinear time unless triangle detection does; 1-use REWBs admit an O(n log squared n) algorithm.
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Allow Me Into Your Dream: A Handshake-and-Pull Protocol for Sharing Mixed Realities in Spontaneous Encounters
TouchPort collapses the multi-stage process of discovering, consenting to, and syncing mixed reality encounters into one embodied handshake-and-pull gesture.
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EnactToM: An Evolving Benchmark for Functional Theory of Mind in Embodied Agents
EnactToM is an evolving benchmark of embodied multi-agent tasks that tests functional Theory of Mind by requiring agents to act optimally on implicit beliefs in partially observable 3D environments.
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Gradual Voluntary Participation: A Framework for Participatory AI Governance in Journalism
The study proposes the Gradual Voluntary Participation (GVP) framework to reconceptualize participatory AI governance in journalism as a gradual and voluntary process using a bidimensional matrix.
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Evaluation-driven Scaling for Scientific Discovery
SimpleTES scales test-time evaluation in LLMs to discover state-of-the-art solutions on 21 scientific problems across six domains, outperforming frontier models and optimization pipelines with examples like 2x faster LASSO and new Erdos constructions.
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Raven: Rethinking Automated Assessment for Scratch Programs via Video-Grounded Evaluation
Raven automates Scratch program assessment by having instructors specify task-level video generation rules and using LLMs to analyze resulting videos for behavioral compliance, outperforming prior tools on real student submissions.
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Developing an AI Concept Envisioning Toolkit to Support Reflective Juxtaposition of Values and Harms
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
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Exploring the non-convexity in machine learning using quantum-inspired optimization
A quantum-inspired global search method called QIEO outperforms traditional solvers in recovering sparse structures and robust fitting by maintaining a broad view of possible solutions.