Search: “benchmark”

Evaluating Factual Density in Multi-Source RAG: A Study in Medical AI Accuracy

arXiv:2605.31506v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is the current industry standard for grounding AI in real-world facts. Traditional retrieval methods rely on keyw

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Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go

DGX agent

arXiv:2511.10868v2 Announce Type: replace Abstract: Training data imbalance poses a major challenge for code LLMs. Most available data heavily over represents raw opensource code while underrepresenti

model-releasesarxiv-cs-lg

1 Jun 2026

How Far Can You Grow? Characterizing the Extrapolation Frontier of Graph Generative Models for Materials Science

arXiv:2602.09309v2 Announce Type: replace-cross Abstract: Every generative model for crystalline materials harbors a critical structure size beyond which its outputs become unreliable; we call this th

MLIPilot: LLM-Driven Auto-Research for Machine-Learned Interatomic Potentials

arXiv:2605.30889v1 Announce Type: cross Abstract: Constructing production-quality machine-learned interatomic potentials (MLIPs) requires balancing accuracy, dynamical stability, and computational thr

Multi-Agent Teams Hold Experts Back

arXiv:2602.01011v4 Announce Type: replace-cross Abstract: Multi-agent LLM systems are increasingly deployed as autonomous collaborators, where agents interact freely rather than execute fixed, pre-spe

safetyarxiv-cs-ai

Not All Synthetic Data Is Yours to Learn From

arXiv:2605.31126v1 Announce Type: cross Abstract: Can a language model improve from plain text sampled from itself, with no prompts, no teacher, no verifier, and no reward model? Yes, but only when th

Probing Collision Grounding in Vision-Language Models for Safe Human-Robot Collaboration

arXiv:2605.31196v1 Announce Type: cross Abstract: Safe human--robot collaboration requires more than visual description: a monitor must determine whether the robot body is safely separated, already co

Re-examining Low Rank adaptation for private LLM fine-tuning

arXiv:2510.01137v3 Announce Type: replace Abstract: Privacy is a central concern when fine-tuning large language models (LLMs) on sensitive data, and differentially private stochastic gradient descent

Recognizing Co-Speech Gestures in-the-Wild

model-releasesarxiv-cs-cv

arXiv:2605.31589v1 Announce Type: new Abstract: While humans naturally gesture during speech, only a sparse subset of these movements are visually depictive and semantically linked to specific spoken

SAEmnesia: Erasing Concepts in Diffusion Models with Supervised Sparse Autoencoders

arXiv:2509.21379v3 Announce Type: replace-cross Abstract: Concept unlearning in diffusion models is hampered by feature splitting, where concepts are distributed across many latent features, making th

Research

SCOPE: Self-Play via Co-Evolving Policies for Open-Ended Tasks

arXiv:2605.31433v1 Announce Type: new Abstract: Self-play can train language models without external supervision. However, existing methods require rule-checkable answers, leaving open-ended tasks dep

researcharxiv-cs-cl

Send a SCOUT First: Pre-hoc Reasoning for Adaptive Detector Allocation in Prompt-Injection Defense

arXiv:2605.30837v1 Announce Type: cross Abstract: Prompt-injection detectors are heterogeneous: each is strong on a different slice of attacks, and none is always reliable. Yet existing systems still

Agents

Social Reasoning in Machines: Investigating Collective Truth-Seeking Dynamics in Large Language Model Debate

arXiv:2605.30391v1 Announce Type: cross Abstract: Human reasoning has long been theorised to operate socially, not through isolated individual cognition, but through collective adversarial discourse,

agentsarxiv-cs-ai

Steering LLMs? Actually, Sparse Autoencoders can outperform simple baselines

arXiv:2605.31183v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) have been seen as a promising avenue for exploring the internals of Large Language Models (LLMs) and for steering model out

SVI-Bench: A Dynamic Microworld for Strategic Video Intelligence

model-releasesarxiv-cs-cv

arXiv:2605.31529v1 Announce Type: new Abstract: True video intelligence demands more than recognizing what is visible: it requires reasoning about why events unfold, predicting what would change under

TabCausal: Pretraining Across Causal Environments for Tabular Causal Discovery

arXiv:2605.31156v1 Announce Type: new Abstract: Causal discovery aims to recover directed causal relations from observational and interventional data, providing a basis for mechanistic understanding a

Task-Focused Memorization for Multimodal Agents

arXiv:2605.31075v1 Announce Type: new Abstract: Long-term memory is essential for multimodal agents to build coherent experience, accumulate world knowledge, and achieve continual learning. However, c

safetyarxiv-cs-cv

The Geometry of Activity Cliffs: Representation Dependence and Multi-Scale Characterization of Activity Landscapes

arXiv:2605.30831v1 Announce Type: cross Abstract: Activity cliffs, structurally similar compounds with large potency differences, are widely treated as intrinsic features of chemical datasets. We argu

// The Efficiency Frontier // Cool paper on context management. As agents reuse the same documents and histories across many turns, the chea…

// The Efficiency Frontier // Cool paper on context management. As agents reuse the same documents and histories across many turns, the cheapest context strategy is not fixed. This work describes a pr

model-releasesdair-ai--x

31 May 2026

A Computational Method for Solving the Stochastic Joint Replenishment Problem in High Dimensions

arXiv:2511.11830v2 Announce Type: replace-cross Abstract: We consider a discrete-time formulation for a class of high-dimensional stochastic joint replenishment problems. First, we approximate the pro

A Full-Pipeline Framework for Evaluating Membership Inference Attacks in Machine Learning

arXiv:2605.29454v1 Announce Type: new Abstract: While Membership Inference Attacks (MIAs) are the prevailing method for identifying training data, their application has expanded into privacy auditing

AfriScience-MT: Towards Decolonizing Science in Africa through Text Translation

arXiv:2605.29741v1 Announce Type: new Abstract: The dominance of colonial languages in African education and scientific communication limits how hundreds of millions of speakers of African languages a

AlignVid: Training-Free Attention Scaling for Semantic Fidelity in Text-Guided Image-to-Video Generation

model-releasesarxiv-cs-cv

arXiv:2512.01334v2 Announce Type: replace Abstract: Text-guided image-to-video generation has made substantial progress, yet it still struggles to execute text-specified edits that require substantial

Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans

arXiv:2410.10398v3 Announce Type: replace-cross Abstract: As large language models (LLMs) increasingly engage in complex social interactions, ensuring that their behaviors align with human ethical pri

Aryabhata 2: Scaling Reinforcement Learning for Advanced STEM Reasoning

arXiv:2605.28829v1 Announce Type: cross Abstract: Competitive STEM examinations such as JEE and NEET require multi-step symbolic reasoning, precise numerical computation, and deep conceptual understan

applicationsarxiv-cs-ai

Audio Jailbreaks in Large Audio-Language Models: Taxonomy, Attack-Defense Analysis, and Cost-Aware Evaluation

arXiv:2605.30031v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) expand jailbreak risks from token-level prompting to the full speech perception-to-reasoning pipeline, where unsaf

safetyarxiv-cs-ai

Brain-IT-VQA: From Brain Signals to Answers

arXiv:2605.29588v1 Announce Type: cross Abstract: Decoding visual content from fMRI signals recorded while a person views images, and specifically answering questions about the seen images, is a long-

DiffSpot: Can VLMs Spot Fine-Grained Visual Differences in Web Interfaces?

arXiv:2605.29615v1 Announce Type: cross Abstract: Vision-language models (VLMs) have made strong progress on high-level image-text alignment, yet their ability to perceive subtle visual differences re

Research

EMAG: Differentiable 4D Gaussian Mixture Splatting for EEG Spatial Super-Resolution

arXiv:2605.29731v1 Announce Type: new Abstract: High-density electroencephalography (HD-EEG) enables fine-grained measurement of cortical activity but requires expensive hardware and lengthy setup tim

researcharxiv-cs-lg

Evolutionary Dynamics of Cooperation in Next-Generation LLM Agent Systems: A Cross-Provider Empirical Extension

arXiv:2605.29874v1 Announce Type: cross Abstract: Do next-generation LLM agents inherit the cooperative biases documented in their predecessors, or does scale and provider diversity reshape equilibriu

GMOS: Grounding Moving Object Segmentation in 3D Space and Time

arXiv:2605.30352v1 Announce Type: new Abstract: Moving Object Segmentation (MOS) aims to discover, segment, and track objects that move independently of the camera. Current MOS methods, however, exhib

applicationsarxiv-cs-cv

GPF-LiveNews: A Streaming Evaluation Protocol for Group-Conditioned Framing in Large Language Models

arXiv:2605.28848v1 Announce Type: cross Abstract: Deployed language models are evaluated in a non-stationary environment: model versions, retrieval layers, safety systems, and real-world inputs all ch

GPIC: A Giant Permissive Image Corpus for Visual Generation

arXiv:2605.30341v1 Announce Type: cross Abstract: Studying scalable methods for visual generative modeling requires large, accessible, and stable datasets. We introduce GPIC, a Giant Permissive Image

Improving Full Waveform Inversion in Large Model Era

arXiv:2603.00377v2 Announce Type: replace Abstract: Full Waveform Inversion (FWI) is a highly nonlinear and ill-posed problem that aims to recover subsurface velocity maps from surface-recorded seismi

MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models

arXiv:2605.29360v1 Announce Type: new Abstract: Action-conditioned world models are increasingly used as scalable simulators for robot learning, yet current evaluations provide limited evidence that t

Mitigating Hallucination in Vision-Language Models through Barrier-Regulated Adaptive Closed-form Steering

arXiv:2605.29881v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate objects that are not present in the input image, largely because visual grounding weakens as de

Research

One Click per Cell Type Suffices: Training-free Group Interaction for Cell Instance Segmentation

arXiv:2605.29429v1 Announce Type: new Abstract: Cell instance segmentation models trained on cell-specific datasets suffer severe performance drops on out-of-distribution cell types, while interactive

researcharxiv-cs-cv

Opir: Efficient Multi-Task Safety Classification for Toxicity, Jailbreaks, Hate Speech, and Harmful Content

arXiv:2605.29659v1 Announce Type: cross Abstract: Real-time safety filtering for large language model (LLM) applications requires classifiers that can detect unsafe prompts, toxic language, jailbreak

OptSkills: Learning Generalizable Optimization Skills from Problem Archetypes via Cluster-Based Distillation

arXiv:2605.29829v1 Announce Type: new Abstract: Leveraging Large Language Models (LLMs) to automatically formulate and solve optimization problems from natural language has emerged as an efficient par

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning

arXiv:2506.08354v2 Announce Type: replace-cross Abstract: This position paper argues that text embedding research should move beyond surface meaning and embrace implicit semantics as a central modelin

applicationsarxiv-cs-ai

PTCG-Bench: Can LLM Agents Master Pokemon Trading Card Game?

arXiv:2605.29653v1 Announce Type: new Abstract: Given a strategically complex board game, human players can quickly learn to devise strategies after playing a few rounds. Autonomous agents require sim

Tutorials

Reasoning that Travels: Dissecting How Chain-of-Thought Transfers Across Models

arXiv:2605.28913v1 Announce Type: new Abstract: Large reasoning models (LRMs) often generate extensive chain-of-thought (CoT) traces before producing a final answer. As explicit textual artifacts, the

tutorialsarxiv-cs-cl

ReasonOps: Operator Segmentation for LLM Reasoning Traces

arXiv:2605.29192v1 Announce Type: new Abstract: Chain-of-thought traces from large reasoning models can span tens of thousands of tokens, yet we lack a vocabulary for describing their internal structu

RightNow-Arabic-0.5B-Turbo: An Open Sub-1B Arabic Language Model via Vocabulary Injection and Edge-First Deployment

arXiv:2605.28827v1 Announce Type: new Abstract: Open Arabic large language models split into two classes: sub-1B multilingual models that treat Arabic as an afterthought (Qwen2.5-0.5B, Falcon-H1-0.5B)

Selective QA over Conflicting Multi-Source Personal Memory: A Diagnostic Testbed and Method Comparison

arXiv:2605.30087v1 Announce Type: new Abstract: Emerging personal AI agents are moving toward persistent, multi-source memory. This creates an evaluation problem: systems must decide how to use confli

STAMP: Training Explicit Memory for Mobile GUI Agents in Controllable and Scalable Virtual Environments

arXiv:2605.29324v1 Announce Type: new Abstract: Mobile GUI agents excel at immediate reactive control but frequently fail in realistic, long-horizon tasks that require memory. This failure stems from

Test Time Training for Supervised Causal Learning

arXiv:2605.30015v1 Announce Type: cross Abstract: Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from signif

applicationsarxiv-cs-ai

Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation

arXiv:2605.29430v1 Announce Type: new Abstract: Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly important front-end for LLM-based assistants a

safetyarxiv-cs-ai