Search: “benchmark”

S-MARC: Causal Streaming Reasoning for Full-Duplex Conversational Behavior Modeling

arXiv:2602.11065v2 Announce Type: replace-cross Abstract: Human conversation is organized by an implicit chain of thought and manifests as temporally structured conversational behaviors. Capturing thi

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Safety

SafeRx-Agent: A Knowledge-Grounded Multi-Agent Framework for Safe and Explainable Medication Recommendation

DGX agent

arXiv:2605.29146v1 Announce Type: cross Abstract: Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional

safetyarxiv-cs-ai

29 May 2026

SAGE: Segment-Aware Gloss-Free Encoding for Token-Efficient Sign Language Translation

arXiv:2507.09266v2 Announce Type: replace Abstract: Gloss-free Sign Language Translation (SLT) has advanced rapidly, achieving strong performances without relying on gloss annotations. However, these

SAHG: Sector-Anisotropic Hyperbolic Graph Model for Social Bot Detection

arXiv:2605.30166v1 Announce Type: cross Abstract: LLM-driven social bots can generate fluent, human-like text, reducing the discriminative advantage of content-based detection alone. However, coordina

safetyarxiv-cs-lg

Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG

arXiv:2605.29084v1 Announce Type: cross Abstract: A retrieval-augmented generation (RAG) system deployed over a multi-author institutional corpus can give a different answer to the same question depen

SAVAA: Mitigating Hallucinations in LVLMs via Step-wise Adaptive Visual Attention Amplification

arXiv:2602.13600v2 Announce Type: replace Abstract: A line of recent training-free methods for mitigating hallucinations in large vision-language models (LVLMs) operates by amplifying attention to vis

researcharxiv-cs-cv

Applications

Scalable RF Simulation in Generative 4D Worlds

arXiv:2508.12176v2 Announce Type: replace-cross Abstract: Radio Frequency (RF) sensing has emerged as a powerful, privacy-preserving alternative to vision-based methods for various perception tasks. H

applicationsarxiv-cs-ai

Scaling Laws for Agent Harnesses via Effective Feedback Compute

model-releasesarxiv-cs-cl

arXiv:2605.29682v1 Announce Type: new Abstract: Agent harnesses increasingly determine the performance of language-model systems by deciding how models call tools, receive feedback, verify intermediat

SciIntBench: Measuring LLM Compliance with Research Integrity Norms Under Adversarial Framing

arXiv:2605.29468v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to support scientific work, but it is unclear whether they uphold responsible conduct of research (

SCOPE: Prompt Evolution for Enhancing Agent Effectiveness

arXiv:2512.15374v2 Announce Type: replace Abstract: Large Language Model (LLM) agents are increasingly deployed in environments that generate massive, dynamic contexts. However, a critical bottleneck

Semantic and Visual Evidence for Efficient Long-Video Reasoning: A Solution for the HD-EPIC VQA Challenge

arXiv:2605.29402v1 Announce Type: cross Abstract: Understanding long-form egocentric videos remains challenging for multimodal large language models (MLLMs) due to limited context length and insuffici

Sequential Physics-Constrained Neural Operator Forward Modeling for the extit{Norne} Reservoir System

model-releasesarxiv-cs-lg

arXiv:2605.28909v1 Announce Type: new Abstract: We develop a comprehensive mathematical and computational framework for sequential surrogate modeling of three-phase black-oil reservoir dynamics using

SERC: LDPC-Inspired Semantic Error Correction for Retrieval-Augmented Generation

arXiv:2605.28837v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have demonstrated remarkable capabilities, their reliability is significantly compromised by hallucinations. Existi

Applications

Size Transferability of Graph Transformers with Convolutional Positional Encodings

arXiv:2602.15239v2 Announce Type: replace Abstract: Transformers have achieved remarkable success across domains, motivating the rise of Graph Transformers (GTs) as attention-based architectures for g

applicationsarxiv-cs-lg

Agents

SkillBrew: Multi-Objective Curation of Skill Banks for LLM Agents

arXiv:2605.29440v1 Announce Type: cross Abstract: Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on comp

agentsarxiv-cs-ai

SMolLM: Small Language Models Learn Small Molecular Grammar

model-releasesarxiv-cs-lg

arXiv:2605.06322v2 Announce Type: replace Abstract: Language models for molecular design have scaled to hundreds of millions of parameters, yet how they learn chemical grammar is poorly understood. We

Soften the Mask: Adaptive Temporal Soft Mask for Efficient Dynamic Facial Expression Recognition

arXiv:2502.21004v2 Announce Type: replace Abstract: Dynamic Facial Expression Recognition (DFER) facilitates the understanding of psychological intentions through non-verbal communication. Existing me

researcharxiv-cs-cv

Solving Integer Linear Programming with Parallel Tempering

arXiv:2605.29366v1 Announce Type: new Abstract: Integer Linear Programming (ILP) serves as a versatile framework for modeling a wide range of combinatorial optimization problems, typically addressed b

researcharxiv-cs-lg

Spurious Prompts: Can Irrelevant Prompts Steer Large Language Models?

arXiv:2605.29678v1 Announce Type: new Abstract: Large language models are highly sensitive to prompts, but this sensitivity is usually studied through task-relevant instructions, demonstrations, or re

researcharxiv-cs-cl

Statistical Embeddings for Similarity, Retrieval, and Interpretable Alignment of Numeric Tabular Datasets

arXiv:2605.30289v1 Announce Type: new Abstract: Numeric tabular datasets are the dominant data format in scientific practice, yet large language models lack native mechanisms for representing numeric

safetyarxiv-cs-lg

Structure-Aware Text Recognition for Ancient Greek Critical Editions

arXiv:2603.02803v2 Announce Type: replace Abstract: Recent advances in visual language models (VLMs) have transformed end-to-end document understanding. However, their ability to interpret the complex

Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text

arXiv:2605.29076v1 Announce Type: cross Abstract: LLMs have advanced text classification, yet existing paradigms face a trade-off: supervised (label only) fine-tuning is scalable but offers limited re

Survey of End-to-End Multi-Speaker Automatic Speech Recognition for Monaural Audio

arXiv:2505.10975v3 Announce Type: replace-cross Abstract: Monaural multi-speaker automatic speech recognition (ASR) remains challenging due to data scarcity and the intrinsic difficulty of recognizing

SwInception -- Local Attention Meets Convolutions

arXiv:2605.29954v1 Announce Type: new Abstract: Sparse vision transformers have gained popularity as efficient encoders for medical volumetric segmentation, with Swin emerging as a prominent choice. S

TAE: Target-aware enhancer for nighttime UAV tracking

arXiv:2605.29558v1 Announce Type: new Abstract: Severe image degradation under low-light nighttime conditions constitutes a core bottleneck preventing all-day applications for UAV-based single object

TANDEM: Temporal-Aware Neural Detection for Multimodal Hate Speech

arXiv:2601.11178v2 Announce Type: replace Abstract: Social media platforms are increasingly dominated by long-form multimodal content, where harmful narratives are constructed through a complex interp

Teaching Language Models to Check Grounded Claim Factuality with Human Test-Taking Strategies

arXiv:2605.29712v1 Announce Type: cross Abstract: Grounded claim factuality checking is important for large language model (LLM) applications such as retrieval-augmented generation, as it helps users

Temporal Stability and Few-Shot Prompting in Math Task Assessment

arXiv:2605.30151v1 Announce Type: new Abstract: As AI tools become increasingly integrated into educational contexts, questions arise about both their stability over time and their responsiveness to p

Text-Preserving Lossy Text Compression: A Study of Strategic Deletion and LLM Reconstruction

model-releasesarxiv-cs-cl

arXiv:2605.29000v1 Announce Type: new Abstract: Traditional lossless text compression preserves every byte, but its gains on natural language are often modest in realistic operating regimes. We study

The Best of the Two Worlds: Harmonizing Semantic and Hash IDs for Sequential Recommendation

arXiv:2512.10388v2 Announce Type: replace-cross Abstract: Conventional Sequential Recommender Systems (SRS) typically assign unique hash IDs (HID) to construct item embeddings, which mainly capture co

safetyarxiv-cs-ai

The Cognitive Categorical Transformer: Category-Theoretic Inductive Biases for Language Modeling

arXiv:2605.28864v1 Announce Type: new Abstract: The Cognitive Categorical Transformer (CCT) is a 306M-parameter architecture that augments a pretrained GPT-2 Small backbone with cognitively grounded c

The Curse of Helpfulness: Inverse Scaling Law in Robustness to Distractor Instructions via DistractionIF

arXiv:2605.29491v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in agentic and retrieval-augmented generation (RAG) systems, where they must execute user-specifi

The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction

arXiv:2605.29411v1 Announce Type: cross Abstract: Under standard graphical assumptions, the Markov boundary of a target variable is the smallest set of features that renders every other feature redund

The Vision Wormhole: Latent-Space Communication in Heterogeneous Multi-Agent Systems

model-releasesarxiv-cs-cl

arXiv:2602.15382v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) powered by Large Language Models have unlocked advanced collaborative reasoning, yet they remain bottlenecked by discrete

Toward User Preference Alignment in LLM Recommendation via Explicit Context Feedback

arXiv:2605.29141v1 Announce Type: cross Abstract: Traditional recommender systems (RecSys) primarily infer user preferences from implicit signals (such as clicks, watches, and purchases), often neglec

safetyarxiv-cs-ai

Local Ai

Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models

arXiv:2605.29826v1 Announce Type: cross Abstract: Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Langu

local-aiarxiv-cs-ai

TRACE: Toulmin-based Reasoning Assessment through Constructive Elements for LLM CoT Evaluation

arXiv:2605.29656v1 Announce Type: new Abstract: Evaluating open-ended outputs from large language models (LLMs) remains challenging due to the absence of ground truth. Existing metrics rely on final-a

Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning

arXiv:2605.29894v1 Announce Type: new Abstract: Recent progress in computer vision has produced a wide range of powerful specialized models for detection, segmentation, counting, and other visual task

safetyarxiv-cs-cv

Training Deliberative Monitors for Black-Box Scheming Detection

arXiv:2605.29601v1 Announce Type: cross Abstract: As autonomous agents become more capable of performing real-world tasks, distinguishing scheming behavior from benign task pursuit may become a centra

Uncertainty Estimation via Hyperspherical Confidence Mapping

arXiv:2605.05964v2 Announce Type: replace Abstract: Quantifying uncertainty in neural network predictions is essential for high-stakes domains such as autonomous driving, healthcare, and manufacturing

safetyarxiv-cs-lg

Local Ai

Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization

arXiv:2605.30227v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) empower Large Language Models to tackle complex reasoning tasks through collaborative interaction, optimizing their dy

local-aiarxiv-cs-ai

Agents

unix-ctf: Procedural Environments for Unix-Competence Reinforcement Learning

arXiv:2605.29115v1 Announce Type: cross Abstract: Unix competence is the ability to use shell and operating-system primitives as first-class tools, not merely to write programs through a terminal. Cur

agentsarxiv-cs-ai

Unlocking the Working Memory of Large Language Models for Latent Reasoning

arXiv:2605.30343v1 Announce Type: cross Abstract: To improve the reasoning capabilities of large language models, test-time compute is typically scaled by generating intermediate tokens before the fin

Local Ai

Unsupervised Semantic Segmentation Facilitates Model Understanding

arXiv:2605.29691v1 Announce Type: new Abstract: Self-supervised learning (SSL) has produced a diverse landscape of vision transformers (ViTs) whose pretrained representations support a wide range of d

local-aiarxiv-cs-cv

Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization

arXiv:2605.29153v1 Announce Type: cross Abstract: Neural networks trained under different hyperparameter settings can fall into distinct training 'regimes,' with consistent behavior within regimes and

User-Aware Active Knowledge Acquisition for Emotional Support Dialogue

arXiv:2605.29715v1 Announce Type: new Abstract: Emotional support plays an important role in dialogue systems, and its success depends on adapting to a user's evolving and implicit needs across multi-

safetyarxiv-cs-cl

VE2VF: Vision-Enabled to Vision-Free Distillation via Real-world Reinforcement Learning for Robust Contact-Rich Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.29564v1 Announce Type: new Abstract: When using reinforcement learning (RL) for contact-rich robotic manipulation, vision can provide task-relevant information that accelerates learning bey

Agents

VikingMem: A Memory Base Management System for Stateful LLM-based Applications

arXiv:2605.29640v1 Announce Type: new Abstract: Large Language Models have revolutionized interactive applications; however, their finite context windows pose a critical data management challenge for

agentsarxiv-cs-ai