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[2501.05765] Deontic Temporal Logic for Formal Verification of AI Ethics
Ai Safety

[2501.05765] Deontic Temporal Logic for Formal Verification of AI Ethics

Abstract page for arXiv paper 2501.05765: Deontic Temporal Logic for Formal Verification of AI Ethics

arXiv - AI · 4 min ·
[2410.19733] ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations
Llms

[2410.19733] ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations

Abstract page for arXiv paper 2410.19733: ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations

arXiv - AI · 3 min ·
[2305.09840] Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning

[2305.09840] Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning

Abstract page for arXiv paper 2305.09840: Scale-Adaptive Balancing of Exploration and Exploitation in Classical Planning

arXiv - AI · 4 min ·
[2405.18248] Extreme Value Monte Carlo Tree Search for Classical Planning

[2405.18248] Extreme Value Monte Carlo Tree Search for Classical Planning

Abstract page for arXiv paper 2405.18248: Extreme Value Monte Carlo Tree Search for Classical Planning

arXiv - AI · 3 min ·
[2603.26660] Ruka-v2: Tendon Driven Open-Source Dexterous Hand with Wrist and Abduction for Robot Learning
Robotics

[2603.26660] Ruka-v2: Tendon Driven Open-Source Dexterous Hand with Wrist and Abduction for Robot Learning

Abstract page for arXiv paper 2603.26660: Ruka-v2: Tendon Driven Open-Source Dexterous Hand with Wrist and Abduction for Robot Learning

arXiv - AI · 4 min ·
[2603.26648] Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification
Llms

[2603.26648] Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification

Abstract page for arXiv paper 2603.26648: Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification

arXiv - AI · 3 min ·
[2603.26556] When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models
Machine Learning

[2603.26556] When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models

Abstract page for arXiv paper 2603.26556: When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models

arXiv - AI · 4 min ·
[2603.26567] Beyond Code Snippets: Benchmarking LLMs on Repository-Level Question Answering
Llms

[2603.26567] Beyond Code Snippets: Benchmarking LLMs on Repository-Level Question Answering

Abstract page for arXiv paper 2603.26567: Beyond Code Snippets: Benchmarking LLMs on Repository-Level Question Answering

arXiv - AI · 4 min ·
[2603.26551] Beyond MACs: Hardware Efficient Architecture Design for Vision Backbones
Computer Vision

[2603.26551] Beyond MACs: Hardware Efficient Architecture Design for Vision Backbones

Abstract page for arXiv paper 2603.26551: Beyond MACs: Hardware Efficient Architecture Design for Vision Backbones

arXiv - AI · 4 min ·
[2603.26639] Make Geometry Matter for Spatial Reasoning
Llms

[2603.26639] Make Geometry Matter for Spatial Reasoning

Abstract page for arXiv paper 2603.26639: Make Geometry Matter for Spatial Reasoning

arXiv - AI · 4 min ·
[2603.26610] Think over Trajectories: Leveraging Video Generation to Reconstruct GPS Trajectories from Cellular Signaling
Generative Ai

[2603.26610] Think over Trajectories: Leveraging Video Generation to Reconstruct GPS Trajectories from Cellular Signaling

Abstract page for arXiv paper 2603.26610: Think over Trajectories: Leveraging Video Generation to Reconstruct GPS Trajectories from Cellu...

arXiv - AI · 4 min ·
[2603.26571] Generation Is Compression: Zero-Shot Video Coding via Stochastic Rectified Flow
Machine Learning

[2603.26571] Generation Is Compression: Zero-Shot Video Coding via Stochastic Rectified Flow

Abstract page for arXiv paper 2603.26571: Generation Is Compression: Zero-Shot Video Coding via Stochastic Rectified Flow

arXiv - AI · 3 min ·
[2603.26539] How Open Must Language Models be to Enable Reliable Scientific Inference?
Llms

[2603.26539] How Open Must Language Models be to Enable Reliable Scientific Inference?

Abstract page for arXiv paper 2603.26539: How Open Must Language Models be to Enable Reliable Scientific Inference?

arXiv - AI · 3 min ·
[2603.26542] The Multi-AMR Buffer Storage, Retrieval, and Reshuffling Problem: Exact and Heuristic Approaches
Nlp

[2603.26542] The Multi-AMR Buffer Storage, Retrieval, and Reshuffling Problem: Exact and Heuristic Approaches

Abstract page for arXiv paper 2603.26542: The Multi-AMR Buffer Storage, Retrieval, and Reshuffling Problem: Exact and Heuristic Approaches

arXiv - AI · 4 min ·
[2603.26498] Rocks, Pebbles and Sand: Modality-aware Scheduling for Multimodal Large Language Model Inference
Llms

[2603.26498] Rocks, Pebbles and Sand: Modality-aware Scheduling for Multimodal Large Language Model Inference

Abstract page for arXiv paper 2603.26498: Rocks, Pebbles and Sand: Modality-aware Scheduling for Multimodal Large Language Model Inference

arXiv - AI · 4 min ·
[2603.26425] CPUBone: Efficient Vision Backbone Design for Devices with Low Parallelization Capabilities
Machine Learning

[2603.26425] CPUBone: Efficient Vision Backbone Design for Devices with Low Parallelization Capabilities

Abstract page for arXiv paper 2603.26425: CPUBone: Efficient Vision Backbone Design for Devices with Low Parallelization Capabilities

arXiv - AI · 4 min ·
[2603.26515] JAL-Turn: Joint Acoustic-Linguistic Modeling for Real-Time and Robust Turn-Taking Detection in Full-Duplex Spoken Dialogue Systems
Llms

[2603.26515] JAL-Turn: Joint Acoustic-Linguistic Modeling for Real-Time and Robust Turn-Taking Detection in Full-Duplex Spoken Dialogue Systems

Abstract page for arXiv paper 2603.26515: JAL-Turn: Joint Acoustic-Linguistic Modeling for Real-Time and Robust Turn-Taking Detection in ...

arXiv - AI · 4 min ·
[2603.26458] Can AI Models Direct Each Other? Organizational Structure as a Probe into Training Limitations
Machine Learning

[2603.26458] Can AI Models Direct Each Other? Organizational Structure as a Probe into Training Limitations

Abstract page for arXiv paper 2603.26458: Can AI Models Direct Each Other? Organizational Structure as a Probe into Training Limitations

arXiv - AI · 4 min ·
[2603.26330] Mitigating the Reasoning Tax in Vision-Language Fine-Tuning with Input-Adaptive Depth Aggregation
Llms

[2603.26330] Mitigating the Reasoning Tax in Vision-Language Fine-Tuning with Input-Adaptive Depth Aggregation

Abstract page for arXiv paper 2603.26330: Mitigating the Reasoning Tax in Vision-Language Fine-Tuning with Input-Adaptive Depth Aggregation

arXiv - AI · 3 min ·
[2603.26410] Why Models Know But Don't Say: Chain-of-Thought Faithfulness Divergence Between Thinking Tokens and Answers in Open-Weight Reasoning Models
Machine Learning

[2603.26410] Why Models Know But Don't Say: Chain-of-Thought Faithfulness Divergence Between Thinking Tokens and Answers in Open-Weight Reasoning Models

Abstract page for arXiv paper 2603.26410: Why Models Know But Don't Say: Chain-of-Thought Faithfulness Divergence Between Thinking Tokens...

arXiv - AI · 4 min ·