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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Dennett.The Intentional Stance
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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.
Local attention strictly enlarges the class of regular languages recognizable by fixed-precision transformers by adding a second past operator in linear temporal logic, with global and local attention being expressively complementary.
Bonsai compiles queries to pruned tree traversals by deriving pruning conditions with extended symbolic interval analysis and fusing compound queries into single traversals.
EnactToM benchmark reveals frontier AI models achieve 0% on functional Theory of Mind task completion in embodied multi-agent settings despite 45% average on literal belief probes.
TouchPort collapses the multi-stage process of discovering, consenting to, and syncing mixed reality encounters into one embodied handshake-and-pull gesture.
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.
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.
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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Deciding DFA-Primality is NP-Hard
Deciding DFA primality is NP-hard, established by reduction from propositional satisfiability using a characterization of primality for a relevant class of automata.
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Characterizing the Expressivity of Local Attention in Transformers
Local attention strictly enlarges the class of regular languages recognizable by fixed-precision transformers by adding a second past operator in linear temporal logic, with global and local attention being expressively complementary.
-
Bonsai: Compiling Queries to Pruned Tree Traversals
Bonsai compiles queries to pruned tree traversals by deriving pruning conditions with extended symbolic interval analysis and fusing compound queries into single traversals.
-
EnactToM: An Evolving Benchmark for Functional Theory of Mind in Embodied Agents
EnactToM benchmark reveals frontier AI models achieve 0% on functional Theory of Mind task completion in embodied multi-agent settings despite 45% average on literal belief probes.
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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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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.
-
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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Instantiating Bayesian CVaR lower bounds in Interactive Decision Making Problems
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.
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Prints in the Magnetic Dust: Robust Similarity Search in Legacy Media Images Using Checksum Count Vectors
Checksum Count Vectors enable robust similarity search to identify duplicate and variant legacy media recordings with high accuracy despite substantial data damage.
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Evolution With Purpose: Hierarchy-Informed Optimization of Whole-Brain Models
Hierarchy-informed curricular optimization of heterogeneous whole-brain models enables generalization to new subjects and prediction of behavioral abilities from parameters.
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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.