arXiv AI
Jun 19
Spatial-Aware Reduction Framework: Towards Efficient and Faithful Visual State Space Models
arXiv:2606. 19932v1 Announce Type: cross Abstract: Mamba demonstrates strong efficiency in modeling long visual sequences.
Benchmarks and evaluation
Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv AI
Jun 19
Cost-Optimal LLM Routing with Limited User Feedback under User Satisfaction Guarantees
arXiv:2606. 19376v1 Announce Type: cross Abstract: Inference costs for large language model (LLM) applications are rapidly growing, driven by surging demand and rising infrastructure cost.
arXiv AI
Jun 19
Zero-Inflated Gaussian Distributions Enable Parameter-Space Sparsity in Estimation-of-Distribution Algorithms
arXiv:2606. 19369v1 Announce Type: cross Abstract: Estimation-of-distribution algorithms (EDAs) are a powerful class of evolutionary methods for black-box optimization, especially when little is known about the structure of the objective.
arXiv AI
Jun 19
StaminaBench: Stress-Testing Coding Agents over 100 Interaction Turns
arXiv:2606. 19613v1 Announce Type: cross Abstract: We introduce StaminaBench, a benchmark that measures the stamina of coding agents: how many consecutive interaction turns (change requests) they can handle before failing.
arXiv AI
Jun 19
FAPO: Fully Autonomous Prompt Optimization of Multi-Step LLM Pipelines
arXiv:2606. 19605v1 Announce Type: cross Abstract: Multi-step LLM pipelines fail through interactions among retrieval, reasoning, and formatting steps, so prompt-only optimization can miss bottlenecks in the chain.
arXiv AI
Jun 19
Multi-LCB: Extending LiveCodeBench to Multiple Programming Languages
arXiv:2606. 20517v1 Announce Type: new Abstract: LiveCodeBench (LCB) has recently become a widely adopted benchmark for evaluating large language models (LLMs) on code-generation tasks.
arXiv AI
Jun 19
FlowEdit: Associative Memory for Lifelong Pronunciation Adaptation in Flow-Matching TTS
arXiv:2606. 20518v1 Announce Type: new Abstract: Flow-matching text-to-speech systems achieve remarkable zero-shot quality but remain static after deployment: pronunciation errors on out-of-vocabulary proper nouns persist unless the model is retrained.
arXiv AI
Jun 19
Rethinking Shrinkage Bias in LLM FP4 Pretraining: Geometric Origin, Systemic Impact, and UFP4 Recipe
arXiv:2606. 20381v1 Announce Type: new Abstract: FP4 training promises substantial reductions in memory and computation cost for LLM pretraining, yet current FP4 hardware paths and recipes, including NVIDIA Blackwell/Rubin-class systems and AMD MI350-series GPUs, remain centered on E2M1 data elements.
arXiv AI
Jun 19
Lagrange: An Open-Vocabulary, Energy-Based Sparse Framework for Generalized End-to-End Driving
arXiv:2606. 20274v1 Announce Type: new Abstract: Scaling end-to-end autonomous driving to complex, open-world environments requires perceptual models that generalize to anomalous scenarios and planners that produce kinematically valid trajectories.
arXiv AI
Jun 19
Navigating Unreliable Parametric and Contextual Knowledge: Explicit Knowledge Conflict Resolution for LLM Inference
arXiv:2606. 20245v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance across a wide range of language-based tasks by leveraging both extensive parametric knowledge and in-context learning ability, enabling them to incorporate external information provided in the input prompt.
arXiv AI
Jun 19
Implicit Semantic-Aware Communication Based on Hypergraph Reasoning
arXiv:2606. 20162v1 Announce Type: new Abstract: Semantic-aware communication has emerged as a transformative paradigm for next-generation communication systems, shifting the fundamental goal from transmitting bit-level symbols to reliably recovering and understanding the semantic meaning of information.
arXiv Machine Learning
Jun 19
Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation
arXiv:2606. 20118v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies have shown strong potential for general-purpose manipulation, yet they often fail on novel, out-of-distribution objects whose appearance or geometry deviates from the training distribution.
arXiv Machine Learning
Jun 19
Thermodynamic Signatures of Reasoning: Free-Energy and Spectral-Form-Factor Diagnostics for Hallucination Detection in Large Language Models
arXiv:2606. 19404v1 Announce Type: new Abstract: Hallucination detection in large language models (LLMs) is deployment-critical, and recent work shows that the spectrum of attention-derived graph Laplacians carries strong signal about reasoning quality.
arXiv AI
Jun 19
IHBench: Evaluating Post-Interruption Recovery in Voice Agents with Structured Workflows
arXiv:2606. 19595v1 Announce Type: cross Abstract: Voice agents deployed in structured workflows (customer service, healthcare scheduling, account management) must handle frequent user interruptions while maintaining progress through multi-step procedures.
arXiv Machine Learning
Jun 19
TetriServe: Efficiently Serving Mixed DiT Workloads
arXiv:2510. 01565v4 Announce Type: replace Abstract: Diffusion Transformer (DiT) models excel at generating high-quality images through iterative denoising steps, but serving them under strict Service Level Objectives (SLOs) is challenging due to their high computational cost, particularly at larger resolutions.
arXiv AI
Jun 19
ELVA: Exploring Ranking-Driven Universal Multimodal Retrieval
arXiv:2606. 20280v1 Announce Type: cross Abstract: Leveraging Multimodal Large Language Models (MLLMs) via contrastive learning has become a mainstream paradigm for improving the performance of Universal Multimodal Retrieval (UMR).
arXiv Machine Learning
Jun 19
Stochastic Linear Contextual Bandits with Bounded Noise: A Set-Membership Approach
arXiv:2606. 20022v1 Announce Type: cross Abstract: This paper considers stochastic linear contextual bandits (SLCB) with bounded reward noise.
arXiv AI
Jun 19
Multi-View Decompilation for LLM-Based Malware Classification
arXiv:2606. 20436v1 Announce Type: cross Abstract: Malware analysts often inspect compiled binaries through decompiled pseudo-C, when source code is unavailable.
arXiv AI
Jun 19
TerraMind: Large-Scale Generative Multimodality for Earth Observation
arXiv:2504. 11171v5 Announce Type: replace-cross Abstract: We present TerraMind, the first any-to-any generative, multimodal foundation model for Earth observation (EO).
arXiv Machine Learning
Jun 19
DADP: Domain Adaptive Diffusion Policy
arXiv:2602. 04037v3 Announce Type: replace Abstract: Learning domain adaptive policies that can generalize to unseen transition dynamics, remains a fundamental challenge in learning-based control.