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Detecting Safety Violations Across Many Agent Traces C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts ClawGUI: A Unified Framework for Training, Evaluating, and Deploying GUI Agents General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks Discourse Diversity in Multi-Turn Empathic Dialogue Evaluating Cooperation in LLM Social Groups through Elected Leadership SWE-AGILE: A Software Agent Framework for Efficiently Managing Dynamic Reasoning Context Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical Systems Legal2LogicICL: Improving Generalization in Transforming Legal Cases to Logical Formulas via Diverse Few-Shot Learning Playing Along: Learning a Double-Agent Defender for Belief Steering via Theory of Mind RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agents A Triadic Suffix Tokenization Scheme for Numerical Reasoning Synthius-Mem: Brain-Inspired Hallucination-Resistant Persona Memory Achieving 94.4% Memory Accuracy and 99.6% Adversarial Robustness on LoCoMo Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment Policy Split: Incentivizing Dual-Mode Exploration in LLM Reinforcement with Dual-Mode Entropy Regularization METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models Quantization Dominates Rank Reduction for KV-Cache Compression Anthropogenic Regional Adaptation in Multimodal Vision-Language Model Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning Learning from Contrasts: Synthesizing Reasoning Paths from Diverse Search Trajectories Do LLMs Know Tool Irrelevance? 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The Shortcomings of Force-from-Motion in Robot Learning
Elie Aljalbout, Felix Frank, Patrick van der Smagt, Alexandros P · 2024-07-03 · via cs.AI updates on arXiv.org

Robotic manipulation requires accurate motion and physical interaction control. However, current robot learning approaches focus on motion-centric action spaces that do not explicitly give the policy control over the interaction. In this paper, we discuss the repercussions of this choice and argue for more interaction-explicit action spaces in robot learning.

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