Search: “models”

Diversity is Not Ambiguity: Toward Accurate and Efficient Ambiguity Detection for Open-Domain QA

arXiv:2608.03177v1 Announce Type: new Abstract: How can question answering (QA) systems determine whether a query is ambiguous? Ambiguity detection is essential in open-domain QA, as misclassification

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Model Releases

EditFlow3D: Automated Local Editing of 3D Assets with Trajectory Preservation

DGX agent

arXiv:2608.03179v1 Announce Type: new Abstract: Controllable local editing of 3D assets requires precise target localization and appropriate visual guidance. However, existing methods lack a simple ye

model-releasesarxiv-cs-cv

5 Aug 2026

Evaluation Blindness: How Silent Measurement Failures Corrupt AI Systems from Training to Deployment

arXiv:2608.02786v1 Announce Type: new Abstract: AI systems can fail silently. The failure propagates through training loops, evaluation pipelines, and production monitoring stacks until downstream har

Fail-Fast, Restart-Smart: Early Failure Prediction and Restart for SWE Agentic Tasks

arXiv:2608.03222v1 Announce Type: cross Abstract: Software engineering (SWE) agents resolve repository-level issues through long trajectories that grow increasingly expensive as context accumulates. F

FedCritic-MIMO: Communication-Efficient Serverless Federated Critic Learning for Massive-MIMO Resource Control in Open and Disaggregated 6G RANs

arXiv:2608.03852v1 Announce Type: new Abstract: This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource c

Forecasting Revenue with its Customer-Base Drivers: When and Why Coordination Helps

arXiv:2608.02911v1 Announce Type: new Abstract: Revenue forecasts guide acquisition budgets, demand planning, and customer-based valuations, yet an aggregate forecast does not show whether change refl

Frozen High-Resolution Inference for Cross-City Object Detection: An AI City Challenge 2026 Study

model-releasesarxiv-cs-cv

arXiv:2608.03136v1 Announce Type: new Abstract: Cross-city object detection requires a detector trained in one city to generalize to an unlabeled target city. In AI City Challenge 2026 Track 6, we ana

GDPevo: Evaluating Agent Self-Evolution on Real Business Tasks

arXiv:2608.03764v1 Announce Type: new Abstract: Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-ev

Tutorials

GraspMeanFlow: SE(3)-Equivariant MeanFlow for Few-Step 6-DoF Grasp Generation

arXiv:2608.03295v1 Announce Type: new Abstract: Recent data-driven methods for synthesizing 6-DoF grasp poses use generative models to learn complex grasp pose distributions and generate diverse candi

tutorialsarxiv-cs-ro

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol

HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification

arXiv:2608.03966v1 Announce Type: new Abstract: Large language models can generate fluent Arabic answers while introducing factual errors that are difficult to identify and verify. Existing Arabic hal

researcharxiv-cs-cl

Agents

IR2Solve: Structured Intermediate Representations for Cost-Efficient Optimization Autoformulation

arXiv:2608.02641v1 Announce Type: cross Abstract: Large language models (LLMs) can translate natural-language optimization problems into solver-ready formulations, but direct code generation is brittl

agentsarxiv-cs-ai

Agents

LiveEvalBench: Toward Open-World Evaluation for Web Generation

arXiv:2608.03689v1 Announce Type: new Abstract: Large language models are increasingly capable of synthesizing executable frontend projects, yet existing benchmarks still treat web generation as a sta

agentsarxiv-cs-ai

Hardware

LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs

arXiv:2608.03036v1 Announce Type: cross Abstract: Large Language Models (LLMs) are integrated into software systems and AI services, making efficient LLM serving a concern for software engineering. Se

hardwarearxiv-cs-ai

LoCA: Forward-Only LLM Tuning after One-Shot Calibration with Local Credit Assignment

arXiv:2608.03020v1 Announce Type: new Abstract: Parameter-efficient post-training reduces the number of trainable parameters, but still requires repeated end-to-end backpropagation through the frozen

Maglev: Sliding Recurrent Memory

arXiv:2608.02870v1 Announce Type: new Abstract: We introduce ours{}, a recurrent Transformer architecture with fixed-size memory that generalizes sliding-window attention while remaining parallelizabl

Measurement Without Validity: The Compounding Reliability Problem in Agentic AI Evaluation

arXiv:2608.00794v2 Announce Type: replace Abstract: Agentic AI evaluation pipelines produce benchmark scores that justify deployment decisions, safety certifications, and regulatory compliance claims.

Tutorials

MIMIC-MJX: Neuromechanical Emulation of Animal Behavior

arXiv:2511.20532v3 Announce Type: replace-cross Abstract: The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavi

tutorialsarxiv-cs-ai

Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue

arXiv:2608.03142v1 Announce Type: cross Abstract: We study contextual dynamic pricing with arbitrary covariate sequences and bounded, possibly nonbinary purchase quantities. Demand follows a semiparam

On the Implicit Flatness Bias of Sharpness-Aware Minimization: A Linear Stability Analysis with Quantitative Hyperparameter Bounds

arXiv:2608.03197v1 Announce Type: new Abstract: Sharpness-Aware Minimization (SAM) improves generalization by seeking parameters whose loss is robust to local adversarial perturbations, but the quanti

On the missing benchmarks layer and a potential solution

arXiv:2608.02996v1 Announce Type: new Abstract: Latin America is missing a foundational layer for native AI development: the benchmark layer. The benchmark layer does two things no other layer can - i

One-Point Contraction: Erasing Representational Separability toward Irreversible Deep Forgetting

arXiv:2507.07754v3 Announce Type: replace-cross Abstract: Machine unlearning is usually evaluated by what the classifier outputs: forget-set accuracy, confidence, membership-inference scores. We show

Output-Aware Rotation for INT2 KV-Cache Quantization

arXiv:2608.02691v1 Announce Type: cross Abstract: The key-value (KV) cache has become a major memory and bandwidth bottleneck in long-context large language model inference, making ultra-low-bit quant

Safety

Predicting Multilingual Classification and Translation Performance of LLMs with Cross-Lingual Alignment nicode{x2013} Is English Enough?

arXiv:2608.03446v1 Announce Type: new Abstract: Multilingual large language models (LLMs) have been shown to perform better on non-English classification tasks when the representations of the given la

safetyarxiv-cs-cl

Predictive Enhancement Calibration for Latent Breast MRI Virtual Contrast Enhancement

model-releasesarxiv-cs-cv

arXiv:2608.03612v1 Announce Type: cross Abstract: Virtual contrast enhancement (VCE) synthesizes enhanced breast MR images from pre-contrast acquisitions. Modern latent generators offer strong image p

PRISMA: Improving the Accuracy-Latency Frontier of Diffusion-based PDE Solvers Using Physics-Informed Spectral Attention

arXiv:2512.01370v2 Announce Type: replace-cross Abstract: Diffusion-based solvers for partial differential equations (PDEs) are often bottle-necked by slow gradient-based test-time optimization routin

Local Ai

Probing Character-level Transformers for the Spanish L-shaped Morphome

arXiv:2608.03452v1 Announce Type: new Abstract: When a transformer learns an irregular morphological pattern, what has it learned? Our test case is the Spanish L-shaped morphome, a complex irregular p

local-aiarxiv-cs-cl

Provably Learning Multi-Head Attention with Queries

arXiv:2608.03294v1 Announce Type: new Abstract: We study the problem of learning multi-head softmax attention from black-box input-output access. The learner may query arbitrary real-valued token sequ

SciRet: A Compute-Aware Empirical Study of Retrieval and Reranking for Scientific RAG

arXiv:2608.03860v1 Announce Type: cross Abstract: We introduce SciRet, a compute-aware empirical study of retrieval-augmented generation for scientific question answering over CORD-19. Rather than pro

SeCo-SBIR: Semantically Consistent Prompt Learning for Zero-Shot Sketch-Based Image Retrieval

arXiv:2608.03120v1 Announce Type: new Abstract: Adapting CLIP for zero-shot sketch-based image retrieval (ZS-SBIR) via prompt learning faces a fundamental tension: the model must bridge the sketch-pho

researcharxiv-cs-cv

Local Ai

SEER: A Self-Grounded Evidence Interface for Controlled Spatial Relation Classification

arXiv:2608.03631v1 Announce Type: new Abstract: Spatial relation questions require a model to identify the queried subject and object before comparing their layout. Yet a VLM can recognize both entiti

local-aiarxiv-cs-cv

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs

model-releasesarxiv-cs-cl

arXiv:2608.03573v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) exhibit fundamentally different behaviors in enhancing multi-task reasoning for large langu

Local Ai

Stochastic Multiple Shooting Trajectory Optimization via Sequential Local Policy Evaluation

arXiv:2608.03978v1 Announce Type: new Abstract: Stochastic single shooting trajectory optimization methods such as Model Predictive Path Integral control (MPPI) have been widely adopted in robotics du

local-aiarxiv-cs-ro

STREAM-VAE: Dual-Path Routing for Slow and Fast Dynamics in Vehicle Telemetry Anomaly Detection

arXiv:2511.15339v3 Announce Type: replace-cross Abstract: Automotive telemetry data exhibits slow drifts and fast spikes, often within the same sequence, making reliable anomaly detection challenging.

Taming the Implicit: Dual-Channel Risk-Aware Reinforcement Fine-Tuning for Continual Multimodal Post-Training

arXiv:2608.03660v1 Announce Type: new Abstract: Reinforcement fine-tuning (RFT) is widely believed to inherently resist catastrophic forgetting in continual post-training of multimodal large language

Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores

arXiv:2608.02985v1 Announce Type: cross Abstract: The standard check for contamination in LLM backtests is simple: compare scores before and after the training cutoff. We show this check is uninformat

researcharxiv-cs-cl

Test-Time Scaling in Reasoning LLMs: Inference Regimes, Evaluation, and Reproducibility

arXiv:2608.04001v1 Announce Type: cross Abstract: Large language models can solve substantially harder reasoning problems with more inference-time compute. The term 'test-time scaling,' however, now c

Safety

The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems

arXiv:2608.03214v1 Announce Type: new Abstract: Large language models have transformed artificial intelligence from isolated prediction services into components of long-running, distributed systems th

safetyarxiv-cs-ai

Towards a new paradigm of scientific discovery with socialized artificial intelligence

arXiv:2608.02775v1 Announce Type: new Abstract: Scientific discovery has advanced through successive transformations in the organization of knowledge. Observation and experimentation established the e

Applications

Trajectory-Guided Forget-Recover Network for Continual LLM Unlearning

arXiv:2608.03123v1 Announce Type: cross Abstract: Machine unlearning aims to eliminate the influence of sensitive data on a model. In the real world, unlearning requests arrive continually, which give

applicationsarxiv-cs-ai

Uncovering Spontaneous Physics Representations in In-Context Learning

arXiv:2508.12448v2 Announce Type: replace-cross Abstract: In-context learning (ICL) lets large language models (LLMs) solve new tasks from prompts alone, across an ever-widening range of domains, yet

UniGD: A Unified Generative-Discriminative Framework for Industrial Retrieval

arXiv:2608.03150v1 Announce Type: new Abstract: Generative retrieval (GR) is a promising paradigm for industrial search advertising, yet its deployment is constrained by strict relevance and latency r

VIBE: Vector Index Benchmark for Embeddings

arXiv:2505.17810v2 Announce Type: replace Abstract: Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines, and rigorous benchmarking is essen

When Correct Solutions Repeat: Rarity-Aware Credit Redistribution for GRPO

arXiv:2608.03467v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) com- monly optimizes each correct completion as an independent learning signal. In GRPO, this comp

When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives

arXiv:2608.03722v1 Announce Type: new Abstract: Collective intelligence research treats disagreement as evidence of epistemic diversity: if agents express different views, the group should retain capa

A Comparative Analysis of MLP and Kolmogorov-Arnold Networks (KAN) for Faster-than-Nyquist (FTN) Signaling Detection

arXiv:2608.02062v1 Announce Type: cross Abstract: Faster-than-Nyquist signaling improves spectral ef- ficiency by deliberately introducing inter-symbol interference. Classical sequence detectors such

4 Aug 2026

A Simple Approximation to the Distribution of the Ridge Regression Estimator

arXiv:2608.02539v1 Announce Type: cross Abstract: We present a simple Gaussian approximation to the finite-sample distribution of the classical ridge regression estimator. Our approximation captures t

4 Aug 2026

Adaptive Reconstruction of Bosonic Quantum States

arXiv:2608.02049v1 Announce Type: cross Abstract: Bosonic quantum systems provide a hardware-efficient platform for quantum information processing but remain challenging to characterise due to their l