Search: “benchmark”

AdaptSplat: Adapting Vision Foundation Models for Feed-Forward 3D Gaussian Splatting

arXiv:2605.10239v1 Announce Type: new Abstract: This work explores a simple yet powerful lightweight adapter design for feed-forward 3D Gaussian Splatting (3DGS). Existing methods typically apply comp

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AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning

DGX agent

arXiv:2410.13181v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality

local-aiarxiv-cs-cl

12 May 2026

Additive Atomic Forests for Symbolic Function and Antiderivative Discovery

arXiv:2605.08130v1 Announce Type: new Abstract: We present a framework for the simultaneous symbolic recovery of a function and its antiderivative from data. The framework rests on three ideas. First,

researcharxiv-cs-lg

Agent-Omit: Adaptive Context Omission for Efficient LLM Agents

arXiv:2602.04284v2 Announce Type: replace Abstract: Managing agent context (e.g., thought and observation) during multi-turn agent-environment interactions is an emerging strategy to improve agent eff

AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators

arXiv:2605.08647v1 Announce Type: cross Abstract: Multi-agent systems achieve state-of-the-art outcomes through peer collaboration. However, when an agent in the pipeline silently drops a constraint,

AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems

arXiv:2605.08715v1 Announce Type: cross Abstract: LLM-based multi-agent systems are increasingly deployed on long-horizon tasks, but a single decisive error is often accepted by downstream agents and

Agents

Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread

agentsarxiv-cs-ai

AIPO: : Learning to Reason from Active Interaction

arXiv:2605.08401v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have demonstrated remarkable reasoning capabilities, largely stimulated by Reinforcement Learning with

Alice v1: Distillation-Enhanced Video Generation Surpassing Closed-Source Models

arXiv:2605.08115v1 Announce Type: cross Abstract: Wepresent Alice v1, a 14-billion parameter open-source video generation model that achieves state-of-the-art quality through consistency distillation

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving

arXiv:2601.01762v2 Announce Type: replace-cross Abstract: Practical autonomous driving requires models that generalize by reasoning through spatial-temporal possibilities to exclude unsafe outcomes. W

An Efficient Token Compression Framework for Visual Object Tracking

arXiv:2605.08329v1 Announce Type: new Abstract: Refining visual representations by eliminating their internal feature-level redundancy is crucial for simultaneously optimizing the performance and comp

An Empirical Study of Multi-Agent Collaboration for Automated Research

arXiv:2603.29632v2 Announce Type: replace-cross Abstract: As AI agents evolve, the community is rapidly shifting from single Large Language Models (LLMs) to Multi-Agent Systems (MAS) to overcome cogni

AnomalyClaw: A Universal Visual Anomaly Detection Agent via Tool-Grounded Refutation

arXiv:2605.10397v1 Announce Type: cross Abstract: Visual anomaly detection (VAD) is crucial in many real-world fields, such as industrial inspection, medical imaging, infrastructure monitoring, and re

Tutorials

APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generation

arXiv:2605.09492v1 Announce Type: cross Abstract: Large language models (LLMs) often suffer from hallucinations due to error accumulation in autoregressive decoding, where suboptimal early token choic

tutorialsarxiv-cs-ai

Are vision-language models ready to zero-shot replace supervised classification models in agriculture?

arXiv:2512.15977v3 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly proposed as general-purpose solutions for visual recognition tasks, yet their reliability for agricul

Agents

ASIA: an Autonomous System Identification Agent

arXiv:2605.10480v1 Announce Type: new Abstract: Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theor

agentsarxiv-cs-ai

Tutorials

Attention Drift: What Autoregressive Speculative Decoding Models Learn

arXiv:2605.09992v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by drafting future tokens with a small model, but drafter models degrade sharply under template perturb

tutorialsarxiv-cs-ai

Attention Grounded Enhancement for Visual Document Retrieval

arXiv:2511.13415v2 Announce Type: replace-cross Abstract: Visual document retrieval requires understanding heterogeneous and multi-modal content to satisfy implicit information needs. Recent advances

AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

arXiv:2509.08031v3 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and non-standardized too

AUHead: Realistic Emotional Talking Head Generation via Action Units Control

arXiv:2602.09534v2 Announce Type: replace Abstract: Realistic talking-head video generation is critical for virtual avatars, film production, and interactive systems. Current methods struggle with nua

Auto-Rubric as Reward: From Implicit Preferences to Explicit Multimodal Generative Criteria

arXiv:2605.08354v1 Announce Type: new Abstract: Aligning multimodal generative models with human preferences demands reward signals that respect the compositional, multi-dimensional structure of human

Automated Detection of Abnormalities in Zebrafish Development

arXiv:2605.10464v1 Announce Type: new Abstract: Zebrafish embryos are a valuable model for drug discovery due to their optical transparency and genetic similarity to humans. However, current evaluatio

BabelDOC: Better Layout-Preserving PDF Translation via Intermediate Representation

arXiv:2605.10845v1 Announce Type: cross Abstract: As global cross-lingual communication intensifies, language barriers in visually rich documents such as PDFs remain a practical bottleneck. Existing d

Agents

Batch-of-Thought: Cross-Instance Learning for Enhanced LLM Reasoning

arXiv:2601.02950v3 Announce Type: replace Abstract: Current Large Language Model reasoning systems process queries independently, discarding valuable cross-instance signals such as shared reasoning pa

agentsarxiv-cs-ai

BetaEdit: Null-Space Constrained Sequential Model Editing

arXiv:2605.09285v1 Announce Type: new Abstract: Null-space-based methods have garnered considerable attention in model editing by constraining updates to the null space of the pre-existing knowledge r

researcharxiv-cs-cl

Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMs

arXiv:2605.09268v1 Announce Type: cross Abstract: Users interacting with Large Language Models (LLMs) in a multi-turn conversation routinely refine their requests or pivot to new topics. LLMs, however

Beyond Hard Writes and Rigid Preservation: Soft Recursive Least-Squares for Lifelong LLM Editing

arXiv:2601.15686v2 Announce Type: replace Abstract: Model editing updates a pre-trained LLM with new facts or rules without retraining while preserving unrelated behavior. In real deployment, edits ar

researcharxiv-cs-lg

Beyond Language: Format-Agnostic Reasoning Subspaces in Large Language Models

arXiv:2605.09496v1 Announce Type: new Abstract: Large language models represent the same reasoning in vastly different surface forms -- English prose, Python code, mathematical notation -- yet whether

Beyond Penalization: Diffusion-based Out-of-Distribution Detection and Selective Regularization in Offline Reinforcement Learning

arXiv:2605.08202v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) faces a critical challenge of overestimating the value of out-of-distribution (OOD) actions. Existing methods miti

Beyond Position Bias: Shifting Context Compression from Position-Driven to Semantic-Driven

arXiv:2605.09463v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated exceptional performance across diverse tasks. However, their deployment in long-context scenarios faces h

safetyarxiv-cs-cl

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models

arXiv:2605.09134v1 Announce Type: new Abstract: Reinforcement learning for program repair is hindered by sparse execution feedback and coarse sequence-level rewards that obscure which edits actually f

Break the Brake, Not the Wheel: Untargeted Jailbreak via Entropy Maximization

arXiv:2605.10764v1 Announce Type: cross Abstract: Recent studies show that gradient-based universal image jailbreaks on vision-language models (VLMs) exhibit little or no cross-model transferability,

Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces

arXiv:2602.08616v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) is increasingly applied to large-scale decision-making problems like logistics, scheduling, and recommender system

Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning

arXiv:2605.08271v1 Announce Type: cross Abstract: Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving

arXiv:2605.10744v1 Announce Type: new Abstract: Safety-critical planning in complex environments, particularly at urban intersections, remains a fundamental challenge for autonomous driving. Existing

CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs

arXiv:2605.09823v1 Announce Type: cross Abstract: We introduce CalBench, a controlled evaluation environment for studying multi-agent coordination through calendar scheduling. In CalBench, N agents ea

Calibrate, Don't Curate: Label-Efficient Estimation from Noisy LLM Judges

arXiv:2605.09702v1 Announce Type: cross Abstract: Multi-judge evaluation is increasingly used to assess LLMs and reward models, and the prevailing heuristic is to curate: keep the most accurate judges

researcharxiv-cs-cl

Can LLMs Predict Polymer Physics Just by Reading Synthesis and Processing Prose?

arXiv:2605.08255v1 Announce Type: cross Abstract: Can large language models predict physical and mechanical polymer properties simply by reading unstructured scientific prose? Polymer performance is r

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key

arXiv:2605.06638v2 Announce Type: replace Abstract: Reinforcement learning (RL) has been applied to improve large language model (LLM) reasoning, yet the systematic study of how training scales with t

Can We Go Beyond Visual Features? Neural Tissue Relation Modeling for Relational Graph Analysis in Non-Melanoma Skin Histology

arXiv:2512.06949v3 Announce Type: replace Abstract: Histopathology image segmentation is essential for delineating tissue structures in skin cancer diagnostics, but modeling spatial context and inter-

CDS4RAG: Cyclic Dual-Sequential Hyperparameter Optimization for RAG

arXiv:2605.08333v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is sensitive to the vast hyperparameters of the retriever and generator, yet optimizing them using given queries

CHAINTRIX: A multi-pipeline LLM-augmented framework for automated smart-contract security auditing

arXiv:2605.09350v1 Announce Type: new Abstract: Smart-contract exploits have caused billions of USD in cumulative losses, yet audits remain expensive and slow. Automated tools have emerged to close th

Chebyshev Center-Based Direction Selection for Multi-Objective Optimization and Training PINNs

arXiv:2605.09975v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) are a promising approach for solving partial differential equations (PDEs). Their training, however, is often d

researcharxiv-cs-lg

CLEAR: Context-Aware Learning with End-to-End Mask-Free Inference for Adaptive Video Subtitle Removal

arXiv:2603.21901v2 Announce Type: replace Abstract: Video subtitle removal aims to distinguish text overlays from background content while preserving temporal coherence. Existing diffusion-based metho

CLEF: EEG Foundation Model for Learning Clinical Semantics

arXiv:2605.10817v1 Announce Type: new Abstract: Clinical EEG interpretation requires reasoning over full EEG sessions and integrating signal patterns with clinical context. Existing EEG foundation mod

CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubrics

arXiv:2605.09584v1 Announce Type: cross Abstract: Inpatient clinical reasoning is a sequential decision under partial observability: the clinician sees the admission so far and must choose the next ac

CMKL: Modality-Aware Continual Learning for Evolving Biomedical Knowledge Graphs

arXiv:2605.10510v1 Announce Type: cross Abstract: Biomedical knowledge graphs are increasingly large, dynamic, and multimodal, driven by rapid advances in biotechnology such as high-throughput sequenc

CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis

arXiv:2510.11233v3 Announce Type: replace Abstract: Depression is a pressing global public health issue, yet publicly available Chinese-language resources for depression risk detection remain scarce a