Search: “models”

Whose Name Comes Up? II: Benchmarking and Intervention-Based Auditing of LLM-Based Scholar Recommendation

arXiv:2602.08873v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now used for academic expert recommendation. Existing audits typically evaluate such recommendations in isola

3 Jun 2026

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Model Releases

AgentProcessBench: Diagnosing Step-Level Process Quality in Tool-Using Agents

DGX agent

arXiv:2603.14465v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have evolved into tool-using agents, they remain brittle in long-horizon interactions. Unlike mathematical reason

model-releasesarxiv-cs-ai

2 Jun 2026

[AINews] NVIDIA Cosmos 3, Nemotron 3 Ultra, and RTX Spark

model-releaseslatent-space

NVIDIA announced three new offerings: Cosmos 3, an advanced video generation model; Nemotron 3 Ultra, an upgraded language model; and RTX Spark, likely a tool or framework for developers. These releas

ARCA: Adapter-Residual Credit Assignment When Token Signals Degenerate

arXiv:2606.00257v1 Announce Type: cross Abstract: Token-level credit assignment for language-model reinforcement learning is usually formulated as if the policy were fully trainable, while practical L

Tutorials

Before the Model Learns the Bug:Fuzzing RLVR Verifiers

arXiv:2606.01066v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) replaces human preference labels with executable reward functions such as math answer checkers, JS

tutorialsarxiv-cs-ai

Chameleon: Style-Content Disentangled Framework for Cross-Domain Object Compositing

arXiv:2606.01079v1 Announce Type: new Abstract: Image compositing aims to seamlessly insert a foreground object into a background image, and recent advances in diffusion models have significantly enha

Collaborative and Efficient Fine-tuning: Leveraging Task Similarity

arXiv:2602.07218v2 Announce Type: replace-cross Abstract: Adaptability has been regarded as a central feature in the foundation models, enabling them to effectively acclimate to unseen downstream task

CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems

arXiv:2606.00756v1 Announce Type: new Abstract: Deploying lightweight Large Language Model (LLM) agents on edge servers can reduce latency and move agentic services closer to users, but resource-const

CultureForest: Understanding and Evaluating Cultural Norm Grounded Reasoning in LLMs

arXiv:2606.01879v1 Announce Type: new Abstract: Existing research largely reduces cultural intelligence in LLMs to a knowledge-level problem, overlooking whether models can effectively utilize their a

FACT: A Simple and Efficient Framework for Active Finetuning

arXiv:2606.02079v1 Announce Type: new Abstract: The main goal of active finetuning is to improve a pretrained model's performance on a specific task or domain by finetuning it with carefully selected

Feature to Dynamics: Feature-space to Autoregression strategy for Zero-shot Time Series Forecasting

arXiv:2606.01289v1 Announce Type: new Abstract: Zero-shot time series forecasting aims to predict future values for previously unseen series, requiring models to generalize temporal dynamics beyond th

From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction

arXiv:2511.12081v2 Announce Type: replace-cross Abstract: Despite massive investments in scale, deep models for click-through rate (CTR) prediction often exhibit rapidly diminishing returns -- a stark

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling

arXiv:2606.00110v1 Announce Type: new Abstract: Achieving robust generalization from limited data is a central challenge in embodied intelligence. Prevailing methods fail by regressing absolute coordi

researcharxiv-cs-cv

Safety

Grounding or Guessing? Visual Signals for Detecting Hallucinations in Sign Language Translation

arXiv:2510.18439v3 Announce Type: replace Abstract: Hallucination, where models generate fluent text unsupported by visual evidence, remains a major flaw in vision-language models and is particularly

safetyarxiv-cs-cl

HakushoBench: A Japanese Chart and Table VQA Benchmark from Governmental White Papers

arXiv:2606.01132v1 Announce Type: new Abstract: Understanding chart and table images is essential for applying vision-language models (VLMs) to real-world document understanding. While English benchma

Hidden Thoughts Are Not Secret: Reasoning Trace Exposure in LLMs

arXiv:2606.00642v1 Announce Type: new Abstract: Reasoning traces have become a valuable form of learning signals for improving and transferring the capabilities of large language models. In particular

How to Correctly Report LLM-as-a-Judge Evaluations

arXiv:2511.21140v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are widely used as scalable evaluators of model responses in lieu of human annotators. However, imperfect sensiti

Improving IoT Intrusion Detection Through SMOTE-Based Oversampling and Extended Multi-Model Evaluation on Side-Channel Power Data

arXiv:2606.00161v1 Announce Type: cross Abstract: The detection of intrusions in IoT-based networks poses challenges that cannot be overcome using traditional machine learning methods. Perhaps the big

Safety

Isolating LLM Lexical Bias: A Curation-Free Triangulated Metric for Preference-Stage Learning

arXiv:2606.00334v1 Announce Type: cross Abstract: Various language domains have undergone remarkable changes in recent years; these shifts are largely attributed to the advent of Large Language Models

safetyarxiv-cs-ai

Logit Distillation on Manifolds: Mapping by Learning

arXiv:2606.00771v1 Announce Type: cross Abstract: A simple way to improve the performance of almost any machine learning model is not to train a single but several models with diverse algorithms which

MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

arXiv:2606.02470v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and too

PaintBench: Deterministic Evaluation of Precise Visual Editing

arXiv:2606.00188v1 Announce Type: cross Abstract: While current multimodal models are proficient at open-ended visual editing, executing precise single-answer edits remains an important obstacle. To p

Local Ai

PEACE: A Planner-Executor Agent with Constraint Enforcement for UAVs

arXiv:2606.00104v1 Announce Type: cross Abstract: Foundation models are increasingly used to drive autonomous systems, yet existing approaches either keep the model in a tight control loop, raising la

local-aiarxiv-cs-ai

ProductWebGen: Benchmarking Multimodal Product Webpage Generation

arXiv:2606.01022v1 Announce Type: cross Abstract: Crafting a product display webpage from a source product image, along with layout and visual content instructions, holds significant practical value f

ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression

arXiv:2606.00494v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) and Low-Rank Adaptation (LoRA) constitute the standard pipeline for efficient Large Language Model (LLM) deployment. Ho

Prototypicality Bias Reveals Blindspots in Multimodal Evaluation Metrics

arXiv:2601.04946v3 Announce Type: replace-cross Abstract: Automatic metrics are widely used to evaluate text-to-image models, often replacing human judgment in benchmarking, model selection, and large

Riemannian Optimization for Hadamard Products of Low-Rank Matrices

arXiv:2606.01216v1 Announce Type: new Abstract: The elementwise Hadamard product of two low-rank matrices provides a parameter-efficient model for data with multiplicative structure, but its modeling

Local Ai

Structure Enables Effective Self-Localization of Errors in LLMs

arXiv:2602.02416v2 Announce Type: replace Abstract: Self-correction in language models remains elusive. In this work, we explore whether language models can explicitly localize errors in incorrect rea

local-aiarxiv-cs-ai

Subliminal Learning Is Steering Vector Distillation

arXiv:2606.00995v1 Announce Type: new Abstract: Subliminal learning refers to a student language model acquiring a teacher's traits (e.g. a system-prompted preference for owls) when fine-tuned on the

The Right Inference Strategy Is All You Need: Nearly Training-Free Domain-Wise Inference for EgoCross Challenge

arXiv:2606.00829v1 Announce Type: new Abstract: EgoCross evaluates multimodal large language models on egocentric video question answering under substantial domain shift, where test videos come from s

researcharxiv-cs-cv

Toward accurate RUL and SoH estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights

arXiv:2507.09766v2 Announce Type: replace-cross Abstract: Accurate estimation of Remaining Useful Life (RUL) and State of Health (SoH) is essential for reliable Prognostics and Health Management (PHM)

TravelEval: A Comprehensive Benchmarking Framework for Evaluating LLM-Powered Travel Planning Agents

arXiv:2606.01046v1 Announce Type: new Abstract: The development of Large Language Models (LLMs) has significantly improved travel planning applications, yet evaluating such models is limited by existi

TukaBench: A Culturally Grounded Jailbreak Benchmark for African Languages

arXiv:2606.01322v1 Announce Type: cross Abstract: Safety evaluation of Large Language Models (LLMs) remains heavily English-centric, leaving Low-Resource Languages (LRLs), particularly African ones, c

Variational Learning for Insertion-based Generation

arXiv:2606.02133v1 Announce Type: cross Abstract: Non-monotonic sequence generation methods, such as masked diffusion models, provide a flexible alternative to left-to-right autoregressive modeling by

When Do Attention Circuits Form? Developmental Trajectories of Capability and Attention-Sink Emergence Across Three 1B-ClassArchitectures

arXiv:2606.02378v1 Announce Type: cross Abstract: We track the developmental trajectory of attention-head circuit formation across three 1B-class language models spanning two architecture families (de

3DAE: Binaural Quality Assessment for Audio Novel View Synthesis with Spatial Maps and Benchmark

arXiv:2605.30469v1 Announce Type: cross Abstract: 3D audio and novel-view acoustic synthesis models are usually evaluated with global metrics.However, global metrics often hide where and why binaural

Anchoring LLM Gender Bias to Human Baselines: A Cross-Lingual Audit

arXiv:2605.30804v1 Announce Type: new Abstract: We audit six large language models (LLMs) for gender stereotyping across English, Korean, Chinese, and Japanese. Three were developed primarily for Engl

Automating Formal Verification with Reinforcement Learning and Recursive Inference

arXiv:2605.30914v1 Announce Type: new Abstract: Automated formal verification remains challenging for large language models because data for proof assistants and verification-aware languages is scarce

Can LLM Teams Play What? Where? When?

arXiv:2605.30459v1 Announce Type: new Abstract: Large language models (LLMs) remain limited on tasks requiring indirect reasoning, cultural knowledge, and coordinated hypothesis testing. We investigat

Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution

arXiv:2605.30802v1 Announce Type: cross Abstract: Prediction markets aggregate collective intelligence to forecast uncertain events, but their utility depends on reliable outcome resolution. Existing

Distilling Counterfactual Reasoning from Language to Vision: Causal Graph Guided Post-Training for Video Understanding

arXiv:2511.19923v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have recently shown significant advancements in video understanding, especially in feature alignment, event reas

DTG-Restore: Training-Free Diffusion Refinement for Generative Video Super-Resolution

arXiv:2605.30431v1 Announce Type: new Abstract: Recent progress in video diffusion models has enabled remarkable generative fidelity, yet leveraging these priors for restoration remains limited by the

FAM-Bench: A Multimodal Benchmark for Condition-Aware Food-as-Medicine Reasoning

arXiv:2605.31410v1 Announce Type: new Abstract: Food-as-Medicine requires models to reason beyond what a dish is or what nutrition it contains: they must decide whether a concrete food choice is appro

Safety

Forecasting with Hyper-Trees

arXiv:2405.07836v5 Announce Type: replace Abstract: We introduce Hyper-Trees as a novel framework for modeling time series data using gradient boosted trees. Unlike conventional tree-based approaches

safetyarxiv-cs-lg

Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments

arXiv:2605.31443v1 Announce Type: cross Abstract: We present a regression-adjustment framework designed for the estimation of longitudinal treatment effects in randomized experiments under static regi

researcharxiv-cs-lg

So much great work lately from Nvidia, the 'King of American Open-source AI'! - Crossed 1,000 total public repositories on @huggingface (820…

model-releasesclem-delangue--x

So much great work lately from Nvidia, the 'King of American Open-source AI'! - Crossed 1,000 total public repositories on @huggingface (820 models, 249 datasets & 57 spaces) & almost 60,000 followers

The fully-managed Remote MCP Server for AlloyDB is now Generally Available

model-releasesgoogle-cloud-ai

AI agents possess incredible reasoning capabilities and can perform increasingly complex actions. But the reliability of agentic outcomes depends entirely on the quality of the context they can access

Thinking in Structures: Evaluating Spatial Intelligence in Constraint-Governed Spaces

arXiv:2602.07864v2 Announce Type: replace Abstract: Spatial intelligence is crucial for vision--language models (VLMs), yet many scene-centric benchmarks evaluate unconstrained environments where a si