Search: “benchmark”

arXiv:2607.03333v1 Announce Type: cross Abstract: LLM agents are becoming a common interface for research, coding, and question answering, yet their Thought-Action-Observation loop is often serial: th

hardwarearxiv-cs-ai

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TokSuite: Measuring the Impact of Tokenizer Choice on Language Model Behavior

DGX agent

arXiv:2512.20757v2 Announce Type: replace Abstract: Tokenizers provide the fundamental basis through which text is represented and processed by language models (LMs). Despite the importance of tokeniz

model-releasesarxiv-cs-cl

7 Jul 2026

Toward Efficient Agents: Memory, Tool learning, and Planning

arXiv:2601.14192v2 Announce Type: replace Abstract: Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has conti

Towards Realistic Remote Sensing Dataset Distillation with Discriminative Prototype-guided Diffusion

arXiv:2601.15829v2 Announce Type: replace Abstract: Recent years have witnessed the remarkable success of deep learning in remote sensing image interpretation, driven by the availability of large-scal

TRACE: Capability-Targeted Agentic Training

arXiv:2604.05336v2 Announce Type: replace Abstract: Models often fail to complete agentic tasks because they lack core capabilities required by the target environment. However, mainstream approaches f

TransitNet: A Compact Attention-Augmented Deep Learning Framework for Low-SNR Transit Blind Searches

arXiv:2606.18932v2 Announce Type: replace-cross Abstract: Motivated by the observational incompleteness of intermediate-to-long-period Earth-size planets, we present TransitNet, a compact attention-au

Turbo-Muon: Almost-Orthogonal Pre-Conditioning for Fast Muon Updates

arXiv:2512.04632v2 Announce Type: replace Abstract: Orthogonality-based optimizers, such as Muon, have recently shown strong performance across large-scale training and community-driven efficiency cha

VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

arXiv:2407.11691v5 Announce Type: replace Abstract: We present VLMEvalKit: an open-source toolkit for evaluating large multi-modality models based on PyTorch. The toolkit aims to provide a user-friend

When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue

arXiv:2510.19186v3 Announce Type: replace Abstract: Evaluating conversational AI systems that use external tools is challenging, as errors can arise from complex interactions among user, agent, and to

CoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation

arXiv:2607.02222v1 Announce Type: cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decompositio

Safety

Conditional Inference Trees and Forests for Feature Selection

arXiv:2607.01417v1 Announce Type: new Abstract: Conditional inference trees (CIT) and conditional inference forests (CIF) reduce split-selection bias by testing features before choosing split threshol

safetyarxiv-cs-lg

Embodied.cpp: A Portable Inference Runtime of Embodied AI Models on Heterogeneous Robots

model-releasesarxiv-cs-ro

arXiv:2607.02501v1 Announce Type: new Abstract: Embodied AI models now span vision-language-action (VLA) models and world-action models (WAMs), but practical deployment remains fragmented across model

Generative AI and Federated Learning for Intrusion Detection Systems: A Survey

arXiv:2607.01305v1 Announce Type: cross Abstract: Intrusion Detection Systems (IDSs) are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Interne

IonSense-QKG: A Quantum-Readiness Metadata Framework for Lithium-Ion Battery Dataset Discovery

arXiv:2607.01286v1 Announce Type: new Abstract: Public lithium-ion battery datasets are increasingly used for state-of-health estimation, remaining-useful-life prediction, anomaly detection, electroch

LACUNA: A Testbed for Evaluating Localization Precision for LLM Unlearning

arXiv:2607.02513v1 Announce Type: cross Abstract: LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal met

Agents

Leveraging Metamemory Agent for Enhanced Data-Free Code Generation in Large Language Models

arXiv:2501.07892v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicit

agentsarxiv-cs-ai

MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning

arXiv:2506.09105v3 Announce Type: replace-cross Abstract: We present MetaTT, a Tensor Train (TT) adapter framework for fine-tuning of pre-trained transformers. MetaTT enables flexible and parameter-ef

NarrativeTrack: Evaluating Entity-Centric Reasoning for Narrative Understanding

arXiv:2601.01095v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved impressive progress in vision-language reasoning, yet their ability to understand tempo

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models

arXiv:2607.01977v1 Announce Type: new Abstract: Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, a

PairCoder++: Pair Programming as a Universal Paradigm for Verified Code-Driven Multimodal and Structured-Artifact Generation

arXiv:2607.01883v1 Announce Type: new Abstract: Code is the medium through which large language models generate structured artifacts: charts, scientific figures, vector graphics, CAD models, 3D scenes

Role-Aware Neural Convex Divergence Heads for Asymmetric Representation Learning

arXiv:2607.01762v1 Announce Type: new Abstract: Many representation learning problems involve directed relations, such as lexical entailment, sentence entailment, ontology hierarchy, and citation link

researcharxiv-cs-lg

Self-Gating Attention for Efficient Time Series Forecasting

arXiv:2607.02344v1 Announce Type: cross Abstract: Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal d

Spec-AUF: Accept-Until-Fail Training under Train-Inference Misalignment for Masked Block Drafters

arXiv:2607.01893v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by drafting a block of tokens that the target model verifies left-to-right, committing only t

Structured Gaussian Processes for Uncertainty-Aware Classification of High-Dimensional, Small-Sampled Omics Data

arXiv:2607.02103v1 Announce Type: cross Abstract: Classifying heterogeneous omics data remains a fundamental challenge in computational biology, particularly in high-dimensional, small-sample settings

TUDUM: A Turkish-Thinking Reasoning Pipeline for Qwen3.5-27B

arXiv:2607.01927v1 Announce Type: cross Abstract: This paper presents TUDUM (Turkce Dusunen Uretken Model), a project pipeline for adapting a Qwen-family 27B thinking model toward Turkish reasoning. T

TurnNat: Automatic Evaluation of Turn-Taking Naturalness in Dyadic Spoken Dialogue

arXiv:2607.01345v1 Announce Type: cross Abstract: Turn-taking naturalness is central to full-duplex spoken dialogue systems, yet its automatic evaluation remains limited. Existing evaluations often re

VLSA: Vision-Language-Action Models with Plug-and-Play Safety Constraint Layer

model-releasesarxiv-cs-ro

arXiv:2512.11891v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated remarkable capabilities in generalizing across diverse robotic manipulation tasks. However, de

Will Scaling Improve Social Simulation with LLMs?

arXiv:2607.02464v1 Announce Type: new Abstract: Large Language Model (LLM) social simulations are a promising research method, but they are not yet faithful enough to be adopted widely. In this work,

researcharxiv-cs-cl

ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understanding

arXiv:2604.00767v2 Announce Type: replace Abstract: Wearable human activity recognition (HAR) has made steady progress, yet much of this progress remains grounded in fixed-window, closed-set classific

Cross4D-JEPA: Dense Cross-modal Correspondence Distillation for 4D Point Cloud Representation Learning

arXiv:2607.00514v1 Announce Type: cross Abstract: Automatic understanding of dynamic 4D point clouds, the 3D-point sequences captured over time by depth sensors and LiDAR, is central to robotics and e

DriveVer: Lightweight Trajectory Evaluator as Test-Time Verifier for Autonomous Driving

arXiv:2607.00399v1 Announce Type: new Abstract: End-to-end autonomous driving models often encounter performance bottlenecks, as training-time scaling leads to high computational costs and diminishing

Dual-Confidence Contrastive Decoding for Retrieval-Augmented Generation

arXiv:2607.00570v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) increasingly requires models to answer questions from multiple retrieved documents, where only some sources are rel

GameDevBench: Evaluating Agentic Capabilities Through Game Development

arXiv:2602.11103v2 Announce Type: replace Abstract: Despite rapid progress on coding agents, progress on their multimodal counterparts has lagged behind. A key challenge is the scarcity of evaluation

GEAR-Seg: A Grounded Explainable Agent for Reasoning Segmentation and Data Engine

arXiv:2607.00544v1 Announce Type: new Abstract: Reasoning segmentation requires localizing targets based on complex, implicit queries. Current end-to-end models typically entangle perception and deduc

HieDG: A Hierarchical Discrete Geometry-Guided Framework for Multi-Animal Tracking

arXiv:2607.00494v1 Announce Type: new Abstract: Multi-animal tracking (MAT) is critical for wildlife monitoring and behavioral analysis, yet remains challenging due to uniform appearance, high density

researcharxiv-cs-cv

KAGE-Bench: Fast Known-Axis Visual Generalization Evaluation for Reinforcement Learning

arXiv:2601.14232v2 Announce Type: replace-cross Abstract: Pixel-based reinforcement learning agents often fail under purely visual distribution shift even when latent dynamics and rewards are unchange

Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration

arXiv:2607.00033v1 Announce Type: cross Abstract: Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains ch

Lost in the Tail: Addressing Geographic Imbalance in Urban Visual Place Recognition

arXiv:2607.00090v1 Announce Type: cross Abstract: Urban-scale Visual Place Recognition (VPR) aims to identify the geographic location of a query image by matching it against a geo-tagged database. Whi

MultiSynt/MT: Trillion-Token Multi-Parallel Pre-Training Data Translated Across 36 Languages

arXiv:2607.00890v1 Announce Type: new Abstract: Open web-scale pre-training corpora remain concentrated in English, limiting multilingual LLM development. We introduce MultiSynt/MT, an open synthetic

OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale

arXiv:2602.05711v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures are evolving towards finer granularity to improve parameter efficiency. However, existing MoE designs f

Right in the Right Way: LM Training with Verifiable Rewards and Human Demonstrations

arXiv:2607.01181v1 Announce Type: cross Abstract: RL with verifiable rewards (RLVR) has emerged as a powerful paradigm for training LMs on tasks with well-defined success metrics, such as code generat

Robust 3D Alignment of Generative Reconstructions via Partial Monocular Observations

arXiv:2607.00498v1 Announce Type: new Abstract: Aligning generative 3D reconstructions with partial monocular observations is a critical but under-explored challenge in computer vision. This task is i

StochasT: Learning with Stochastic Turn Depth for Visual Instruction Tuning

arXiv:2607.00465v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) rely extensively on Visual Instruction Tuning (VIT) to elicit their multimodal reasoning capabilities. However, w

Timesynth: A Temporal Fidelity Framework for Health Signal Digital Twins

arXiv:2607.00431v1 Announce Type: new Abstract: Forecasting models for health-signal digital twins must preserve the oscillatory, frequency, phase, and state-transition dynamics of physiological signa

Towards High-Resolution Visual Perception via Hierarchical Entity Exploration

arXiv:2607.00816v1 Announce Type: new Abstract: High-resolution (HR) image perception remains a key challenge in multimodal large language models (MLLMs), as fine-grained details are often lost when t

Towards Metric-Agnostic Trajectory Forecasting

arXiv:2607.01133v1 Announce Type: new Abstract: Accurate trajectory forecasting of surrounding traffic participants is a core capability for autonomous driving, enabling vehicles to anticipate behavio

VolumeDP: Modeling Volumetric Representation for Manipulation Policy Learning

model-releasesarxiv-cs-ro

arXiv:2603.17720v2 Announce Type: replace Abstract: Imitation learning is a prominent paradigm for robotic manipulation. However, existing visual imitation methods map 2D image observations directly t

A swap-adversarial framework for improving domain generalization in electrocorticography-based Parkinson's disease classification

arXiv:2602.10528v2 Announce Type: replace-cross Abstract: We propose a novel swap-adversarial framework that mitigates high inter-subject variability and the high-dimensional low-sample-size problem i