Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization
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New papers, breakthroughs and academic AI research
DVA-Neurons: Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks
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Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching
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Defusing Explosive Prompts: Understanding and Preventing Trigger-Based Prompt Injections in LLM Agents
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HalluTracer: Pre-Decoding Truthfulness Prediction via Depth-Averaged Probe-Logit
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Ada3Drift: Adaptive Training-Time Drifting for One-Step 3D Visuomotor Robotic Manipulation
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TriFleetRCA: On-Premise LLM Root Cause Analysis for Kubernetes
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From Inference Engine to Inference Control Plane: Connecting vLLM, llm-d, and the Evolution of Efficient Distributed LLM Serving
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HearInContext: A Benchmark for Implicit Context in Speech Recognition
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Smarter by the Moment: Environment-Driven Dynamic Policies for Continual LLM Improvement
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Anatomy of a Closed-Loop Collapse: A Causal Case Study of a Compressed VLA Policy
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PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks for PDE Solving via Large Language Models
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