Behavior-Induced Mirror-Prox Temporal-Difference Learning for Faster Off-Policy Prediction
arXiv:2605.28849v1 Announce Type: new Abstract: Gradient temporal-difference methods provide stable off-policy prediction with linear function approximation, but their practical performance…
Preference-Shaped Expected Hypervolume and R2 Improvement: Exact Computation and Monotonicity
arXiv:2605.28746v2 Announce Type: replace-cross Abstract: This paper studies preference-shaped expected improvement criteria for Bayesian multiobjective optimization. We consider two indicator…
HARP: Hadamard-Preconditioned Adaptive Rotation Processor for Extreme LLM Quantization
arXiv:2605.29843v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is essential for deploying LLMs under memory and bandwidth constraints. However, extreme…
CB-SLICE: Concept-Based Interpretable Error Slice Discovery
arXiv:2605.29836v1 Announce Type: cross Abstract: Despite strong average-case performance, deep learning models often exhibit systematic errors on specific population groups,…
QuITE: Query-Based Irregular Time Series Embedding
arXiv:2605.28166v2 Announce Type: replace-cross Abstract: Irregular Multivariate Time Series (IMTS) are common in practice, yet their irregular sampling complicates effective…
On Language Generation in the Limit with Bounded Memory
arXiv:2605.30324v1 Announce Type: cross Abstract: We study language generation in the limit under bounded memory. In this task, a learner…
PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding
arXiv:2605.30126v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) map visual inputs into dense token sequences, imposing a quadratic computational…
AsyncTool: Evaluating the Asynchronous Function Calling Capability under Multi-Task Scenarios
arXiv:2605.27995v2 Announce Type: replace Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve…
Recurrent Structural Policy Gradient for Partially Observable Mean Field Games
arXiv:2602.20141v2 Announce Type: replace Abstract: Mean Field Games (MFGs) provide a principled framework for modelling interactions in large population systems.…
