Search: “benchmark”

Structure of Basic Human Values in Russian Social Media

model-releasesarxiv-cs-cl

arXiv:2603.18822v2 Announce Type: replace Abstract: What is known about the values of national populations rests almost entirely on questionnaires, which prompt respondents to rate researcher-supplied

Switching Linear Attention

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arXiv:2609.39034v1 Announce Type: cross Abstract: Designing expressive sequence layers with efficient inference remains a central challenge in modern machine learning. Standard softmax attention achie

researcharxiv-cs-ai

1 Oct 2026

SynIL: Leveraging Synergy for Offline Imitation Learning from Imperfect Demonstration Datasets

arXiv:2609.38225v1 Announce Type: cross Abstract: Imitation learning enables robots to acquire complex skills directly from massive demonstration datasets, but its performance degrades severely when d

researcharxiv-cs-ai

Synthesis Without Training: An Inference-Only Pipeline for Tabular, Temporal, and Relational Synthetic Data

arXiv:2609.38414v1 Announce Type: new Abstract: Synthetic data generation is dominated by the fit-then-sample paradigm: a generative model is trained on a private dataset and then sampled from. Despit

agentsarxiv-cs-lg

Taming Speculative Search for Test-Time Scaling in LLM Serving

arXiv:2609.39334v1 Announce Type: cross Abstract: Test-time scaling has recently emerged as a powerful approach for improving LLM reasoning by allocating additional computation during inference, subst

researcharxiv-cs-cl

TERRA: Terrain-Aware Reconstruction, Retargeting and Control for Musculoskeletal Locomotion

arXiv:2609.38653v1 Announce Type: cross Abstract: Recent advances in musculoskeletal modeling and reinforcement learning have enabled muscle-actuated agents to reproduce increasingly complex human mot

safetyarxiv-cs-ai

TexTailor: Texture-Preserving Video Virtual Try-On via Adaptive Garment Conditioning

arXiv:2609.39335v1 Announce Type: new Abstract: Video virtual try-on has attracted increasing attention due to its broad potential in digital fashion and intelligent e-commerce. However, existing meth

researcharxiv-cs-cv

The critical distinction between base LLMs (2024 and earlier) and modern LRMs is not symbolic tool use. It's the switch from a transductive …

model-releasesfrancois-chollet--x

The critical distinction between base LLMs (2024 and earlier) and modern LRMs is not symbolic tool use. It's the switch from a transductive paradigm (intuit the answer to the query) to an inductive pa

TopTimeNet: Topologically-assisted time-series classification model

model-releasesarxiv-cs-lg

arXiv:2609.39792v1 Announce Type: new Abstract: Distinguishing periodic from chaotic dynamics in a time series is a fundamental challenge in both physics and engineering. Yet, end-to-end learned archi

Towards Agile Vision-Based Multi-UAV Flight: Revisiting State Estimation

model-releasesarxiv-cs-ro

arXiv:2609.39611v1 Announce Type: new Abstract: Agile multi-UAV flight requires accurate and low-latency onboard estimation of the kinematic states of neighboring UAVs for collision avoidance, motion

Towards Better Exploration in Sequential Test-Time Scaling

arXiv:2609.39632v1 Announce Type: new Abstract: Test-time scaling improves language model reasoning by spending additional compute at inference. However, both classes of existing methods often fail to

researcharxiv-cs-lg

Towards Universal Wasserstein Barycenters through Flow Matching

arXiv:2609.38547v1 Announce Type: cross Abstract: Defining a weighted mean over probability measures under probability metrics is a central tool in probabilistic machine learning. Under the Wasserstei

safetyarxiv-cs-ai

TRACE: Trajectory Selection for Parallel Scaling of Search Agents

arXiv:2609.39912v1 Announce Type: cross Abstract: Parallel search may generate a correct answer that final-answer voting fails to select. We formulate this consolidation stage as trajectory selection

agentsarxiv-cs-ai

Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory

arXiv:2606.19998v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed across diverse tasks, yet they remain black boxes whose physical interactions ca

Tutorials

TripleFlow: Training-Free Video Object Removal by Bridging Residual Editing and Native Generation

arXiv:2609.39157v1 Announce Type: new Abstract: Video object removal presents a uniquely difficult editing challenge. Because a removal prompt specifies only what to erase rather than what to generate

tutorialsarxiv-cs-cv

Tutorials

TSGL: Teacher-Student Graph Learning for 3DGS Compression

arXiv:2609.38635v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) is a popular representation for novel view synthesis. However, 3DGS contains millions of Gaussian primitives, each with r

tutorialsarxiv-cs-cv

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

agentsarxiv-cs-ai

Applications

UBTree: Parallel Tree Drafting via Unigram and Bigram Models for Speculative Decoding

arXiv:2609.39972v1 Announce Type: new Abstract: Speculative decoding accelerates language model inference by verifying multiple draft tokens in a single target-model pass. Recent parallel drafters hav

applicationsarxiv-cs-cl

UniAE-MoE: A Unified Audio Encoder via Mixture of Experts

arXiv:2609.39199v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) rely on effective audio encoders for multi-task performance. We introduce UniAE-MoE, a unified audio encoder desig

UniST-Pred: A Robust Unified Framework for Spatio-Temporal Traffic Forecasting in Transportation Networks Under Disruptions

arXiv:2602.14049v2 Announce Type: replace-cross Abstract: Spatio-temporal traffic forecasting is a core component of intelligent transportation systems, supporting various downstream tasks such as sig

UniWAM Technical Report: Unified Mobile Manipulation via Mixed-Stream World-Action Modeling and Manipulation Anchor Pose Supervision

model-releasesarxiv-cs-cv

arXiv:2609.39388v1 Announce Type: cross Abstract: Mobile manipulation requires precise navigation to a manipulation-ready pose followed by reliable object interaction. These two stages differ in actio

Unlearning Deceptive Behaviors in LLMs with Contrastive Forget Sets

arXiv:2609.38909v1 Announce Type: cross Abstract: Large language models often know the truth and say otherwise: a model that answers correctly when asked neutrally will affirm a user's mistaken belief

researcharxiv-cs-ai

VidHarness: Evolving Agent Harnesses for Cost-Efficient Long Video Understanding

arXiv:2609.38413v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer questions about hour-long videos, but processing every frame is prohibitively expensive, even though the eviden

agentsarxiv-cs-cv

Wavelet Flow Matching for Time Series

arXiv:2609.39374v1 Announce Type: cross Abstract: Synthetic time series are increasingly used for data augmentation, privacy-preserving data sharing, and downstream model development, yet faithfully r

When Context Changes: Understanding Update Failures in LLMs

arXiv:2609.38866v1 Announce Type: new Abstract: As preferences, goals, and facts change, LLM agents must use the current state while earlier versions remain in context. Yet they can answer with an old

Hardware

When Masking Helps or Hurts Robustness in Compressed CLIP: A Pre-Deployment Diagnostic

arXiv:2609.39704v1 Announce Type: cross Abstract: This paper demonstrate that whether masking-based token pruning helps or hurts worst-group robustness can be predicted before deployment, without labe

hardwarearxiv-cs-ai

When, Not How Much: Evaluating Time-Series Foundation Models on Sparse Events

model-releasesarxiv-cs-lg

arXiv:2609.39386v1 Announce Type: new Abstract: Pretrained time-series foundation models (TSFMs) are evaluated as forecasters of future values, yet for sparse series many decisions depend only on whic

Where MLLMs Fail and Why: Causal Task Decomposition for Capability Failure Diagnosis

arXiv:2609.38851v1 Announce Type: cross Abstract: End-to-end accuracy on compositional tasks records how often MLLMs fail, but cannot distinguish whether a failure reflects an intrinsic deficit in the

Where Scientific Search Agents Fail: Decision-Checkpoint Auditing of Exposure and Inspection Attempts

arXiv:2609.38670v1 Announce Type: new Abstract: Final-answer accuracy does not reveal whether a scientific-search agent failed to encounter a target paper, attempt to inspect it, or return an accepted

Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

arXiv:2609.38274v1 Announce Type: new Abstract: The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive

researcharxiv-cs-cl

Whitening Improves Robustness to Spurious Correlations in Linear Probes

arXiv:2609.39177v1 Announce Type: new Abstract: Deep neural networks tend to rely on simple features that may be spurious and thus fail to generalize. We study this problem in the setting of linear pr

researcharxiv-cs-lg

Yggdrasil: a Layer-First 3D Scene Graph for Real-Time Querying

model-releasesarxiv-cs-ro

arXiv:2609.38640v1 Announce Type: new Abstract: Robotic agents use 3D scene graphs (3DSG) to perform tasks ranging from scene understanding to scene interaction. Although an extensive body of work add

A Character-Level Neural Approach to Sinhala Sandhi Splitting

model-releasesarxiv-cs-cl

arXiv:2609.36131v1 Announce Type: new Abstract: Sinhala Sandhi splitting recovers the constituent words or morphemes hidden inside a phonologically merged surface form. The task is important for Sinha

A Comprehensive View of Fairness through Distributional Stability

arXiv:2609.37061v1 Announce Type: cross Abstract: We view fairness as a property of distributional stability. Rather than assessing a predictor under a fixed data distribution, we study how its predic

safetyarxiv-cs-ai

Tutorials

A Digital Simulation Toolkit for Physics-Based Generation of Realistic Experimental Scanning Tunneling Microscopy Images

arXiv:2609.36639v1 Announce Type: new Abstract: Scanning Tunneling Microscopy (STM) is a widely used tool for characterizing surfaces of materials at the atomic scale, playing a crucial role in discov

tutorialsarxiv-cs-lg

A Dual-Track Curation-and-Classification Framework for Resolving Ground-Truth Label Noise in Operational Sentinel-2 Wheat Area Estimation

model-releasesarxiv-cs-cv

arXiv:2609.36975v1 Announce Type: new Abstract: Operational estimation of wheat-cultivated area is persistently constrained by discordance between administrative record-keeping and remotely sensed cla

A Model-Agnostic Physics-Guided Adapter for Few-Shot Transfer of Coastal Flood Prediction Models to Unseen Regions

model-releasesarxiv-cs-lg

arXiv:2609.37565v1 Announce Type: new Abstract: Deep learning surrogates can produce high-resolution coastal flood maps orders of magnitude faster than physics-based hydrodynamic simulators, yet trans

Act First, Reason Later: Accelerating On-Policy Distillation for Multi-Turn Agents via Reference-Conditioned Inverse Dynamics

model-releasesarxiv-cs-cl

arXiv:2609.36608v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains multi-turn language agents with dense teacher supervision on student-generated responses. However, standard think-

ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3

arXiv:2606.16996v2 Announce Type: replace-cross Abstract: Segment Anything Model 3 (SAM 3) provides a strong frozen backbone for concept-prompted segmentation, but applying it directly to open-vocabul

agentsarxiv-cs-ai

Adapting Context Compression for Long-Horizon Agents with Counterfactual Continuations

arXiv:2609.36526v1 Announce Type: cross Abstract: Long-horizon agents require context compression to manage growing interaction histories. Compression quality, however, is ultimately determined by dow

AdaTutoRank: Learning to Rerank Document Sets via Adaptive Tutoring Optimization for RAG and Deep Research

arXiv:2609.32472v2 Announce Type: replace Abstract: Document rerankers determine what evidence reaches the downstream model in RAG and deep research, yet mainstream rerankers select by relevance match

safetyarxiv-cs-cl

Adversarial Debiasing of Machine Learning Models for Enhanced Network Security against DDoS Attacks

arXiv:2609.36167v1 Announce Type: cross Abstract: Distributed Denial of Service attacks are a growing threat to network infrastructure, and new techniques, including the use of generative AI, make the

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations

arXiv:2609.36915v1 Announce Type: cross Abstract: Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities fo

Agentic AI for Scalable and Robust Optical Systems Control

arXiv:2602.20144v2 Announce Type: replace-cross Abstract: We present AgentOptics, an agentic AI framework for high-fidelity, autonomous optical system control built on the Model Context Protocol (MCP)

Agentic Commerce Bench: Measuring Fraud Detection for Agents That Spend Money

arXiv:2609.35886v1 Announce Type: cross Abstract: AI agents now hold spend authority and settle payments without per-action human confirmation. The resulting loss is often not a security failure: a co

Alignment Forecasting: Predicting Misalignment From Training Data

arXiv:2609.35805v1 Announce Type: cross Abstract: Training a language model on data with a narrow flaw can sometimes make the model broadly misaligned. Inspecting the data at face value often does not

Alpha Diffusion Language Models: Factorization Alone Is Not the Problem

arXiv:2609.38066v1 Announce Type: new Abstract: Discrete diffusion language models can generate multiple tokens in parallel, but reducing the number of denoising steps can lead to inconsistent predict

researcharxiv-cs-lg

Anatomy-Aware Prediction of Bronchoscopic Accessibility from 3D CT

model-releasesarxiv-cs-cv

arXiv:2609.37386v1 Announce Type: new Abstract: Pre-operative planning for bronchoscopy is critical for the diagnosis of lung lesions. Current accessibility assessment relies on subjective manual insp