Search: “benchmark”

HiMed: Incentivizing Hindi Reasoning in Medical LLMs

arXiv:2605.24635v1 Announce Type: new Abstract: Medical large language models hold promise for reducing healthcare disparities, yet Hindi remains severely underrepresented. While medical LLMs excel in

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HoloFair: Unified T2I Fairness Evaluation and Fair-GRPO Debiasing

DGX agent

arXiv:2605.24687v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have made significant strides in visual realism and semantic consistency, yet they often perpetuate and amplify societal bi

model-releasesarxiv-cs-ai

26 May 2026

How Many Tools Should an LLM Agent See? A Chance-Corrected Answer

arXiv:2605.24660v1 Announce Type: cross Abstract: Before an LLM agent can use a tool, a retrieval system must decide which candidate tools to show to the agent. How long should that shortlist be? Show

How Should LLMs Consume High-Quality Data? Optimal Data Scheduling via Quality-Aware Functional Scaling Laws

arXiv:2605.25698v1 Announce Type: cross Abstract: High-quality data is scarce in large language model (LLM) training, yet how to schedule its use jointly with training dynamics lacks theoretical guida

Agents

Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning

arXiv:2508.19113v3 Announce Type: replace Abstract: Large reasoning models (LRMs) combined with retrieval-augmented generation (RAG) have enabled deep research agents capable of multi-step reasoning w

agentsarxiv-cs-ai

Hylos: Operability Contracts for Model-Native Spatial Intelligence

arXiv:2605.24728v1 Announce Type: new Abstract: Foundation models can increasingly describe, reconstruct, and generate 3D objects, assemblies, scenes, and environments, but visually plausible spatial

HyperGuide: Hyperbolic Guidance for Efficient Multi-Step Reasoning in Large Language Models

arXiv:2605.24140v1 Announce Type: new Abstract: Multi-step reasoning remains a central challenge for large language models: single-pass generation is efficient but lacks accuracy; tree-search methods

Implicit Binarization via Complex Phase Dynamics in Combinatorial Optimization

arXiv:2605.24502v1 Announce Type: cross Abstract: We introduce a physics-inspired continuous relaxation framework that yields substantially improved solutions for NP-hard combinatorial optimization pr

researcharxiv-cs-lg

Inference Time Optimization with Confidence Dynamics

arXiv:2605.25244v1 Announce Type: new Abstract: Inference time optimization techniques, such as repeated sampling, have significantly advanced the reasoning capabilities of Large Language Models (LLMs

Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization

arXiv:2605.25203v1 Announce Type: cross Abstract: We apply the influence-adaptive Walsh geometry of a companion theory paper (arXiv:2605.01637) to extreme low-bit weight-only LLM quantization. The rec

researcharxiv-cs-ai

Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents

arXiv:2605.25632v1 Announce Type: new Abstract: Autonomous AI agents increasingly issue side-effect-bearing actions: database mutations, refunds, payments, external commitments. We propose the Actuari

InvariantCloud: A Globally Invariant, Uniquely Indexed Point Cloud Framework for Robust 6-DoF Tactile Pose Tracking

arXiv:2605.25216v1 Announce Type: new Abstract: Recent advances in imitation learning and vision-language models highlight the need for high-fidelity tactile perception, with 6-DoF tactile object pose

researcharxiv-cs-ro

Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications

arXiv:2605.24883v1 Announce Type: new Abstract: The widespread integration of Large Language Models (LLMs) necessitates rigorous and systematic safety evaluation. Existing paradigms either rely on con

IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems

arXiv:2605.24339v1 Announce Type: new Abstract: We present IsaacIPC, a robotic simulation framework that couples GPU accelerated incremental potential contact (IPC) with IsaacSim/Lab. IsaacIPC maps si

safetyarxiv-cs-ro

IVR-R1: Refining Trajectories through Iterative Visual-Grounded Reasoning in Reinforcement Learning

arXiv:2605.23997v1 Announce Type: cross Abstract: Multimodal large language models via reinforcement learning (RL) have demonstrated remarkable capabilities in complex visual reasoning tasks, yet they

JacQuant: STE-Free Quantization-Aware Training via Learned Jacobian Surrogates

arXiv:2605.25469v1 Announce Type: new Abstract: Quantization-aware training (QAT) is widely deployed but typically relies on the Straight-Through Estimator (STE), which passes gradients through non-di

JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments

arXiv:2602.18527v2 Announce Type: replace-cross Abstract: Current audio-visual large language models (AV-LLMs) are predominantly restricted to 2D perception, relying on RGB video and monaural audio. T

JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures

arXiv:2602.17162v2 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the 'Laws of Nature'. Whil

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data

arXiv:2605.24414v1 Announce Type: new Abstract: We introduce JT-Safe-V2, a large language model designed to advance the safety and trustworthiness of foundation models, extending our previous JT-Safe

KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI

arXiv:2510.02327v2 Announce Type: replace-cross Abstract: Real-time speech-to-speech (S2S) models excel at generating natural, low-latency conversational responses but often lack deep knowledge and se

Keep the Proof State Live: Snapshotting for Efficient Tactic Search in Lean 4

arXiv:2605.25556v1 Announce Type: cross Abstract: Automated theorem proving systems built on Lean 4 increasingly rely on parallel tactic search over partially specified proofs, such as those generated

Applications

Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversation

arXiv:2605.24647v1 Announce Type: new Abstract: Personalized dialogue requires more than recalling explicit user histories: systems also need to infer hidden user states that evolve through interactio

applicationsarxiv-cs-cl

Learning Fine-grained Parameter Sharing via Sparse Tensor Decomposition

arXiv:2411.09816v4 Announce Type: replace Abstract: Large neural networks achieve state-of-the-art performance on many tasks, yet their sheer size hinders deployment on resource-constrained devices. A

Learning in Low-Dimensional Subspaces: Orthogonal Bottlenecks for Reinforcement Learning

arXiv:2605.26012v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) agents commonly rely on high-dimensional neural representations, despite growing evidence that task-relevant value an

Hardware

Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

arXiv:2602.05052v3 Announce Type: replace Abstract: We present a unified algorithmic framework for the numerical solution, constrained optimization, and physics-informed learning of PDEs with a variat

hardwarearxiv-cs-lg

Learning to Search and Searching to Learn for Generalization in Planning

arXiv:2605.25720v1 Announce Type: new Abstract: Combinatorial generalization remains a central challenge in Deep Reinforcement Learning (DRL). Classical planning provides a simple yet challenging sett

Local Ai

LLM Agent Based Renewable Energy Forecasting Using Edge and IoT Data A Review of Solar Wind Weather and Grid Aware Decision Support

arXiv:2605.25141v1 Announce Type: cross Abstract: Reliable forecasting of renewable energy generation is a foundational requirement for grid stability energy trading battery scheduling and carbon awar

local-aiarxiv-cs-ai

LLMTabBench: Evaluating LLMs on Binary Tabular Classification From Zero to Few Shots

arXiv:2605.24417v1 Announce Type: new Abstract: Supervised classification for tabular data remains a core machine learning task, yet its reliance on large labeled datasets limits applicability in data

Looped Diffusion Language Models

arXiv:2605.26106v1 Announce Type: new Abstract: Masked diffusion models (MDMs) have emerged as a promising alternative to autoregressive models for language modeling, yet the effective design of trans

Applications

LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability

arXiv:2605.24077v1 Announce Type: cross Abstract: Machine learning deployments in real-world wireless communication tasks face significant generalization challenges due to location and environment-spe

applicationsarxiv-cs-lg

Machine Learning Multiscale Interactions

arXiv:2605.25710v1 Announce Type: cross Abstract: Realistic physical systems are characterised by emergent interactions across multiple length and time scales, posing a significant challenge for predi

researcharxiv-cs-lg

MARS: Margin and Semantic-Aware Data Augmentation for Reward Modeling

arXiv:2602.17658v2 Announce Type: replace-cross Abstract: Reward modeling is central to alignment pipelines such as RLHF, RLAIF, and PPO-based policy optimization, yet its reliability is constrained b

Measuring the Depth of LLM Unlearning via Activation Patching

arXiv:2605.24614v1 Announce Type: cross Abstract: Large language model (LLM) unlearning has emerged as a crucial post-hoc mechanism for privacy protection and AI safety, yet auditing whether target kn

MEDAL: Manifold Embedding Distillation via Autoencoder Learning

arXiv:2605.24244v1 Announce Type: cross Abstract: Low-dimensional embeddings are widely used as visual summaries of high-dimensional data and to enable downstream scientific discoveries. Yet, popular

Agents

MemForest: An Efficient Agent Memory System with Hierarchical Temporal Indexing

arXiv:2605.23986v1 Announce Type: cross Abstract: Memory is a fundamental component for enabling long-context LLM agents, supporting persistent state across interactions through a continuous serve-and

agentsarxiv-cs-ai

Memory-Induced Tool-Drift in LLM Agents

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration

arXiv:2605.25030v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems offer a promising approach to reduce hallucinations and improve answer accuracy in large language models (L

MindAlign: Bridging EEG, Vision, and Language for Zero-Shot Visual Decoding

arXiv:2605.24523v1 Announce Type: cross Abstract: Visual decoding from brain signals is a key challenge at the intersection of computer vision and neuroscience, requiring methods that bridge neural re

Minimax Limits of k-Fold Cross-Validation via Majority

arXiv:2605.25859v1 Announce Type: cross Abstract: We study the mean-squared error of k-fold cross-validation as a risk estimator, with particular emphasis on how its accuracy depends on the number of

Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration

arXiv:2605.24957v1 Announce Type: new Abstract: The generation of factually incorrect objects, commonly known as object hallucination, remains a persistent challenge in Large Vision-Language Models (L

researcharxiv-cs-ai

Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling

arXiv:2605.24037v1 Announce Type: cross Abstract: Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures ex

Mosaic: Compositional Multi-Concept Erasure via Vector Field Blending

arXiv:2605.25574v1 Announce Type: cross Abstract: Concept erasure has emerged as a key research direction for ensuring safe and ethical image synthesis in Text-to-Image (T2I) models. While existing st

MuCRASP: Multimodal Chain-of-thought Reasoning aware Structured Pruning

arXiv:2605.25842v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly rely on chain-of-thought (CoT) reasoning to solve complex multimodal tasks, but their large parameter sizes m

MuJoCoUni:Persistent Batched Runtime Primitives for MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.24922v1 Announce Type: new Abstract: We present MuJoCoUni, a downstream MuJoCo distribution for online robot learning and batched physics evaluation. Alongside the open-loop batched traject

Multi-Agent Coordination Adaptation via Structure-Guided Orchestration

arXiv:2605.25746v1 Announce Type: cross Abstract: As large language model (LLM)-based multi-agent systems scale to handle increasingly complex tasks, balancing structural stability and dynamic adaptab

MultiHaluDet: Multilingual Hallucination Detection via LLM Hidden State Probing

arXiv:2605.24919v1 Announce Type: new Abstract: Hallucinations in Large Language Models (LLMs) represent a critical barrier to their reliable deployment, a vulnerability heavily exacerbated in non-Eng

Multimodal Functional Maximum Correlation for Emotion Recognition

arXiv:2512.23076v2 Announce Type: replace-cross Abstract: Emotional states manifest as coordinated yet heterogeneous physiological responses across central and autonomic systems, posing a fundamental

Local Ai

Multiscale Real-Time Object Detection in the NMS-Free Era: A Comparative Performance Evaluation of YOLOv8 and YOLO26

arXiv:2605.24831v1 Announce Type: cross Abstract: Non-Maximum Suppression (NMS) remains a key post-processing step in many real-time object detection pipelines, but it can introduce latency variation

local-aiarxiv-cs-ai