Search: “benchmark”

POLARIS: Guiding Small Models to Write Long Stories

arXiv:2606.04095v1 Announce Type: cross Abstract: Small open-weight models struggle at long-form creative writing: their generated stories either fall far short of the requested length, or their quali

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Proof-Carrying Agent Actions: Model-Agnostic Runtime Governance for Heterogeneous Agent Systems

DGX agent

arXiv:2606.04104v1 Announce Type: cross Abstract: Agent systems execute through runtimes with very different control points: local coding tools, framework SDKs, managed agent platforms, API gateways,

model-releasesarxiv-cs-ai

4 Jun 2026

Query-based Cross-Modal Projector Bolstering Mamba Multimodal LLM

arXiv:2606.04719v1 Announce Type: new Abstract: The Transformer's quadratic complexity with input length imposes an unsustainable computational load on large language models (LLMs). In contrast, the S

Local Ai

Reasoning or Fluency? Dissecting Probabilistic Confidence in Best-of-N Selection

arXiv:2601.13735v2 Announce Type: replace Abstract: Probabilistic confidence metrics are increasingly adopted as proxies for reasoning quality in Best-of-N selection, under the assumption that higher

local-aiarxiv-cs-ai

Reasoning over Boundaries: Enhancing Specification Alignment via Test-time Deliberation

model-releasesarxiv-cs-cl

arXiv:2509.14760v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly applied in diverse real-world scenarios, each governed by bespoke behavioral and safety specifications

Local Ai

Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data

arXiv:2606.04238v1 Announce Type: cross Abstract: Aggressive weight quantization to 2-bit precision offers substantial throughput and memory gains for large language model (LLM) inference, but typical

local-aiarxiv-cs-ai

Reflection Separation from a Single Image via Joint Latent Diffusion

arXiv:2606.04107v1 Announce Type: new Abstract: Single-image reflection separation is highly challenging under extreme conditions like glare or weak reflections. Existing methods often struggle to rec

applicationsarxiv-cs-cv

Representation Matters in Randomized Smoothing for Audio Classification

arXiv:2606.04210v1 Announce Type: cross Abstract: Randomized smoothing (RS) certifies robustness in the vector space where Gaussian noise is added. In audio classification, this space is often not uni

safetyarxiv-cs-lg

Rethinking Incompleteness: Formalizing Protocol Divergence and Train-Once Learning for Robust IMVC

arXiv:2606.04857v1 Announce Type: new Abstract: Standard IMVC evaluation retrains separate models for different missing-data configurations. We show that this paradigm obscures a fundamental vulnerabi

researcharxiv-cs-lg

RUBAS: Rubric-Based Reinforcement Learning for Agent Safety

arXiv:2606.04051v1 Announce Type: cross Abstract: The evolution of LLMs into tool-enabled agents creates a new class of safety challenges associated with real-world execution rather than simple text g

SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding

arXiv:2606.04974v1 Announce Type: new Abstract: Diffusion large language models (DLLMs) enable non-autoregressive generation by iteratively denoising corrupted token sequences with bidirectional conte

SAM 3D: 3Dfy Anything in Images

arXiv:2511.16624v2 Announce Type: replace-cross Abstract: We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single i

SANE Schema-aware Natural-language Evaluation of Biological Data

arXiv:2606.04500v1 Announce Type: new Abstract: High-throughput microscopy generates large, structured datasets capturing cellular responses to pharmacological perturbations, but accessing these datas

Hardware

Scaling Novel Graph Generation via Lightweight Structure-Guided Autoregressive Models

arXiv:2606.04287v1 Announce Type: cross Abstract: Generating realistic and diverse graphs is a key problem in machine learning, with applications in molecular discovery, circuit design, cybersecurity,

hardwarearxiv-cs-ai

Scene-Centric Unsupervised Video Panoptic Segmentation

arXiv:2606.04925v1 Announce Type: new Abstract: Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regio

Self-Evolving Deep Research via Joint Generation and Evaluation

arXiv:2606.04507v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become increasingly adopted in daily applications, with deep research standing out as a particularly important capab

Agents

Self-Reflective APIs: Structure Beats Verbosity for AI Agent Recovery

arXiv:2606.05037v1 Announce Type: cross Abstract: When an AI agent calls an API and hits a validation error, it needs more than what went wrong -- it needs what to do next. A self-reflective API retur

agentsarxiv-cs-ai

Agents

SePO: Self-Evolving Prompt Agent for System Prompt Optimization

arXiv:2606.04465v1 Announce Type: cross Abstract: System prompt optimization improves agent behavior without modifying the underlying model, yielding human-readable, model-agnostic instructions. Exist

agentsarxiv-cs-ai

Shifting the Breaking Point of Flow Matching for Multi-Instance Editing

arXiv:2602.08749v3 Announce Type: replace Abstract: Flow matching models have recently emerged as an efficient alternative to diffusion, especially for text-guided image generation and editing, offeri

SMADE-IE: Sparse Multi-Agent Framework with Evidence-Driven Debate for Zero-Shot Information Extraction

model-releasesarxiv-cs-cl

arXiv:2606.04691v1 Announce Type: new Abstract: Zero-shot information extraction (IE) with large language models (LLMs) has attracted increasing attention due to its flexibility in adapting to new sch

SoLoPO: Unlocking Long-Context Capabilities in LLMs via Short-to-Long Preference Optimization

arXiv:2505.11166v3 Announce Type: replace-cross Abstract: Despite advances in pretraining with extended context sizes, large language models (LLMs) still face challenges in effectively utilizing real-

Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time

arXiv:2504.12329v2 Announce Type: replace-cross Abstract: Recent advances leverage post-training to enhance model reasoning performance, which typically requires costly training pipelines and still su

SPLIT-PINN: Separable Probability Learning Technique via Physics-Informed Neural Networks for High-Dimensional Probabilistic Modeling

model-releasesarxiv-cs-lg

arXiv:2606.04000v1 Announce Type: cross Abstract: We present a probabilistic modeling framework for incorporating small-scale spatial heterogeneity into macroscopic descriptions of material behavior f

SSSD: Simply-Scalable Speculative Decoding

arXiv:2411.05894v3 Announce Type: replace-cross Abstract: Speculative Decoding has emerged as a popular technique for accelerating inference in Large Language Models. However, most existing approaches

applicationsarxiv-cs-ai

StepPRM-RTL: Stepwise Process-Reward Guided LLM Fine-Tuning for Enhanced RTL Synthesis

arXiv:2606.04246v1 Announce Type: new Abstract: Automatic generation of RTL code for digital hardware designs remains challenging due to long-horizon reasoning, multi-step dependencies, and strict cor

Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation

model-releasesarxiv-cs-cl

arXiv:2606.04454v1 Announce Type: new Abstract: Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical

Streaming Communication in Multi-Agent Reasoning

arXiv:2606.05158v1 Announce Type: cross Abstract: Multi-agent reasoning systems adopt a 'generate-then-transfer' paradigm that forces end-to-end latency to scale linearly with pipeline depth. We intro

Structure-Aware Prediction of PROTAC-Mediated Protein Degradability via Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.04021v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) can selectively degrade disease-causing proteins, yet predicting which targets are amenable to degradation re

Supportive Token Revealing for Fast Diffusion Language Model Decoding

arXiv:2606.04236v1 Announce Type: cross Abstract: Discrete diffusion language models can generate text efficiently by updating multiple masked positions in parallel, but this parallelism introduces a

researcharxiv-cs-ai

SymTRELLIS: Symmetry-Enforced Voxel Latents for 3D Generation

arXiv:2606.04108v1 Announce Type: cross Abstract: Single-view 3D generative models have achieved impressive visual quality, yet they are not designed to satisfy structural or functional requirements,

Take a Peek: Efficient Encoder Adaptation for Few-Shot Semantic Segmentation via LoRA

arXiv:2512.10521v2 Announce Type: replace Abstract: Few-shot semantic segmentation (FSS) aims to segment novel classes in query images using only a small annotated support set. While prior research ha

researcharxiv-cs-cv

Local Ai

Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents

arXiv:2606.04555v1 Announce Type: cross Abstract: Long-horizon conversational agents need to interact with users through evolving events, tasks, and goals. Such histories are naturally temporal, yet m

local-aiarxiv-cs-ai

The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning

arXiv:2606.04280v1 Announce Type: cross Abstract: Contrastive learning has become a leading paradigm for self-supervised representation learning, yet the conditions under which it recovers meaningful

Toward Multi-Domain and Long-Tailed Quantization via Feature Alignment and Scaling

arXiv:2606.04920v1 Announce Type: cross Abstract: Quantizing deep neural networks is essential for efficient inference on resource-constrained devices. However, most existing methods are designed for

safetyarxiv-cs-cv

Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification

arXiv:2606.04037v1 Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability bench

Toward Trustworthy Portrait Editing: Evaluation of Demographic Misrepresentation in I2I Models

arXiv:2602.16149v2 Announce Type: replace Abstract: Instruction-guided image-to-image (I2I) editors are increasingly used in consumer and professional visual workflows, where trustworthiness depends n

Towards Evaluating the Robustness of Visual State Space Models

arXiv:2406.09407v3 Announce Type: replace Abstract: Vision State Space Models (VSSMs), a novel architecture that combines the strengths of recurrent neural networks and latent variable models, have de

applicationsarxiv-cs-cv

TPA-AD: A Two-Stage Pseudo Anomaly-Guided Method for Bearing Time-Series Anomaly Detection

arXiv:2606.04073v1 Announce Type: cross Abstract: This paper proposes a two-stage pseudo anomaly-guided anomaly detection method (extbf{T}wo-stage extbf{P}seudo extbf{A}nomaly-guided extbf{A}nomaly ex

researcharxiv-cs-ai

Treat Traffic Like Trees: A Semantic-Preserving Hierarchical Graph-Based Expert Framework for Encrypted Traffic Analysis

arXiv:2606.04517v1 Announce Type: cross Abstract: Graph-based deep learning methods have been widely employed in encrypted traffic analysis to exploit latent correlations across different granularitie

T^star: Progressive Block Scaling for Masked Diffusion Language Models Through Trajectory Aware Reinforcement Learning

arXiv:2601.11214v5 Announce Type: replace Abstract: We present T^star, a simple TraceRL-based training curriculum for progressive block-size scaling in masked diffusion language models (MDMs). Startin

Using Text-Based Causal Inference to Disentangle Factors Influencing Online Review Ratings

arXiv:2606.04286v1 Announce Type: new Abstract: Online reviews provide valuable insights into the perceived quality of facets of a product or service. While aspect-based sentiment analysis has focused

applicationsarxiv-cs-cl

VGGSounder: Audio-Visual Evaluations for Foundation Models

arXiv:2508.08237v4 Announce Type: replace-cross Abstract: The emergence of audio-visual foundation models underscores the importance of reliably assessing their multi-modal understanding. The VGGSound

ViewMask-1-to-3: Multi-View Consistent Image Generation via Multimodal Discrete Diffusion Models

arXiv:2512.14099v3 Announce Type: replace Abstract: Motivated by discrete diffusion's success in language-vision modeling, we explore its potential for multi-view generation, a task dominated by conti

researcharxiv-cs-cv

WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation

arXiv:2606.04907v1 Announce Type: new Abstract: Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policie

safetyarxiv-cs-ro

Weakly Supervised Incremental Segmentation via Semantic Anchors and Spatial Arbitration

arXiv:2606.04060v1 Announce Type: new Abstract: Weakly Incremental Learning for Semantic Segmentation (WILSS) suffers from the continuous introduction of noisy supervision, which progressively corrupt

researcharxiv-cs-cv

What If Prompt Injection Never Left? Exploring Cross-Session Stored Prompt Injection in Agentic Systems

arXiv:2606.04425v1 Announce Type: cross Abstract: Modern agentic systems transform LLMs from session-bounded assistants into stateful systems that persist and evolve shared world state across sessions

XSSR: Cross-Domain Self-Supervised Representative Selection for Efficient Annotation in Medical Image Segmentation

arXiv:2606.04301v1 Announce Type: new Abstract: Acquiring labeled medical image data is resource-intensive and a challenge further exacerbated in cross-domain scenarios where source and target dataset

A formal definition and meta-model for a machine theory of mind