Search: “models”

ATLAS: Agentic Test-time Learning-to-Allocate Scaling

arXiv:2606.01667v1 Announce Type: new Abstract: Test-time scaling has become a major way to improve large language model reasoning, but its orchestration has remained designer-engineered: a fixed samp

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Benchmarking Multimodal LLMs on Code Generation for Complex Interactive Webpages

DGX agent

arXiv:2606.00154v1 Announce Type: cross Abstract: Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyz

model-releasesarxiv-cs-ai

2 Jun 2026

Can LLMs Reason Structurally? Benchmarking via the Lens of Data Structures

arXiv:2505.24069v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are deployed on increasingly complex tasks that require multi-step decision-making. Understanding their algorithm

CityTrajBench: A Unified Benchmark for City-Scale Vehicle Trajectory Generation

arXiv:2606.02287v1 Announce Type: cross Abstract: Urban trajectory generation is a fundamental task for transportation simulation, urban planning, and mobility analytics. However, systematic compariso

Connecting the Dots: Benchmarking Reflective Memory in Long-Horizon Dialogue

arXiv:2606.01223v1 Announce Type: cross Abstract: Despite substantial progress in long-context modeling, existing benchmarks remain confined to factual memory for explicit recall, failing to measure t

Safety

Consistency Training while Mitigating Obfuscation via Rate Matching

arXiv:2606.02211v1 Announce Type: cross Abstract: Large language models are often influenced by extraneous input features, such as cues revealing a user's preferred answer. Consistency training reduce

safetyarxiv-cs-ai

Consistent and Distinctive: LLM Benchmark Efficiency via Maximum Independent Set Prompt Selection on Similarity Graphs

arXiv:2606.01400v1 Announce Type: cross Abstract: Evaluating large language models (LLMs) across comprehensive benchmarks is expensive and time-consuming. We propose a graph-based prompt selection fra

Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedback

arXiv:2606.01081v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictive models by optimizing downstream decision quality rather than standalone prediction accuracy. For conte

Density-Aware Translation of Spurious Correlations in Zero-Shot VLMs

model-releasesarxiv-cs-cv

arXiv:2606.01710v1 Announce Type: new Abstract: Vision-Language models (VLMs), such as CLIP, achieve powerful zero-shot classification. However, their predictions remain sensitive to spurious correlat

Do Text Edits Generalize to Visual Generation? Benchmarking Cross-Modal Knowledge Editing in UMMs

arXiv:2606.00477v1 Announce Type: new Abstract: Unified multimodal models (UMMs) have emerged as a promising paradigm for general-purpose multimodal intelligence. As they are deployed in real-world ap

FineVerify: Scaling Test-Time Compute with Fine-Grained Self-Verification for Agentic Search

arXiv:2606.00660v1 Announce Type: new Abstract: Agentic search requires language model agents to explore many sources and answer complex information-seeking questions. Scaling test-time compute is a p

FVSpec: Real-World Property-Based Tests as Lean Challenges

arXiv:2606.01008v1 Announce Type: cross Abstract: We present a benchmark for evaluating AI models and agents on real-world formal software verification tasks. We first scrape 11,039 property-based tes

GIRL-DETR: Gradient-Isolated Reinforcement Learning for Video Moment Retrieval

arXiv:2606.00775v1 Announce Type: cross Abstract: Video Moment Retrieval (VMR) task requires accurately localizing temporal boundaries aligned with natural language queries, but many models suffer fro

I-WebGenBench : Evaluating Interactivity in LLM-Generated Scientific Web Applications

arXiv:2606.00750v1 Announce Type: new Abstract: Recent advances in visual language models have enabled autonomous agents for complex reasoning, tool use, and document understanding. However, existing

Identifying High-Confidence Social Biases in LLMs for Trustworthy Conversational Tutoring Agents

arXiv:2606.01584v1 Announce Type: cross Abstract: Conversational tutoring agents have been shown to improve learning engagement and student outcomes, and large language models (LLMs) are increasingly

Investigating and Alleviating Harm Amplification in LLM Interactions

arXiv:2606.02423v1 Announce Type: new Abstract: Large language models (LLMs) can serve as helpful assistants, yet they can equally function as harm amplifiers that enable malicious users to achieve ha

'I've Seen How This Goes': Characterizing Diversity via Progressive Conditional Surprise

arXiv:2606.01811v1 Announce Type: cross Abstract: Measuring the diversity of creative outputs is central to evaluating post-training mode collapse, comparing decoding strategies, and quantifying creat

K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts

arXiv:2606.02404v1 Announce Type: new Abstract: Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, b

LK Losses: Direct Acceptance Rate Optimization for Speculative Decoding

arXiv:2602.23881v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to propose candidate t

researcharxiv-cs-cl

LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services

arXiv:2512.07436v3 Announce Type: replace Abstract: Recent advances in large reasoning models LRMs have enabled agentic search systems to perform complex multi-step reasoning across multiple sources.

MM-Snowball: Evaluating and Mitigating Hallucination Snowballing in Multimodal Multi-Turn Dialogue

model-releasesarxiv-cs-cv

arXiv:2606.00622v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) demonstrate remarkable visual understanding, yet their reliability in interactive settings is severely undermin

OmniOPD: Logit-Free On-Policy Distillation via Speculative Verification

arXiv:2606.01476v1 Announce Type: cross Abstract: On-Policy Distillation (OPD) trains a student model on its own generative trajectories under dense token-level feedback from a stronger teacher, mitig

On the Evaluation of Spiking Neural Network Configurations for Network Intrusion Detection

arXiv:2606.01442v1 Announce Type: cross Abstract: Network intrusion detection is a core component of modern cybersecurity infrastructure, yet the deep learning models that dominate the field are compu

Local Ai

One-Shot Crowd Counting With Density Guidance For Scene Adaptation

arXiv:2602.07955v2 Announce Type: replace Abstract: Crowd scenes captured by cameras at different locations vary greatly, and existing crowd models have limited generalization for unseen surveillance

local-aiarxiv-cs-cv

Optimal Regularization for Performative Learning

arXiv:2510.12249v2 Announce Type: replace Abstract: In performative learning, the data distribution reacts to the deployed model - for example, because strategic users adapt their features to game it

PaSBench-Video: A Streaming Video Benchmark for Proactive Safety Warning

arXiv:2606.02443v1 Announce Type: cross Abstract: Between the first visible sign of danger and the moment an accident occurs, there is often a window where intervention remains possible. Video-capable

Pinterest Canvas: Large-Scale Image Generation at Pinterest

arXiv:2603.06453v2 Announce Type: replace Abstract: While recent image generation models demonstrate a remarkable ability to handle a wide variety of image generation tasks, this flexibility makes the

researcharxiv-cs-cv

Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems

arXiv:2606.00052v1 Announce Type: new Abstract: As Industry 4.0 accelerates the integration of Cyber-Physical Systems (CPS) in manufacturing, robust anomaly detection has become critical for ensuring

Reasmory: 3D Reconstruction as Explicit Memory for VLMs Spatial Reasoning

arXiv:2606.00963v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) exhibit emerging spatial reasoning capabilities, yet they remain unreliable on tasks requiring precise spatial understan

ReasonBENCH: Benchmarking the (In)Stability of LLM Reasoning

arXiv:2512.07795v2 Announce Type: replace Abstract: Benchmark scores for LLM reasoning systems are reported as single numbers, yet the same model, strategy, and task can produce meaningfully different

Reconstructing Content via Collaborative Attention to Improve Multimodal Embedding Quality

arXiv:2603.01471v2 Announce Type: replace-cross Abstract: Multimodal embedding models, rooted in multimodal large language models (MLLMs), have yielded significant performance improvements across dive

researcharxiv-cs-lg

Resonant Context Anchoring: Decoupling Attention Routing and Signal Gain at Inference Time

arXiv:2606.01923v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit 'contextual disregard' when faced with input evidence that conflicts with their internal parametric memo

SDR: Set-Distance Rewards for Radiology Report Generation

arXiv:2606.00440v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has rapidly advanced reasoning in vision--language models. However, for chest X-ray report generation, th

Suppressing Forgery-Specific Shortcuts for Generalizable Deepfake Detection

arXiv:2606.01843v1 Announce Type: cross Abstract: Deepfake detection suffers from poor generalization across forgery methods, as existing models tend to rely on spurious method-specific shortcuts that

TCAR-Gen: Temporal Graph Retrieval with Evidence Fusion for Knowledge-Grounded Generation

arXiv:2606.00029v1 Announce Type: cross Abstract: Retrieval-augmented generation systems struggle with temporal reasoning and evidence fusion when answering complex questions over historical criminal

TECCI: Tricky Edits of Collected and Curated Images

arXiv:2606.01213v1 Announce Type: cross Abstract: Despite tremendous recent progress, current text-guided image editing methods still struggle with many aspects of editing involving instruction follow

The Ghost Couple: Correlated LLM Name Priors and Their Haunting of the Web and Academic Publishing

arXiv:2606.02184v1 Announce Type: cross Abstract: These names do not exist. Elena Vasquez and Marcus Chen have appeared as volcano experts, astronauts, thriller protagonists, podcast hosts, and academ

The Image Reconstruction Game: Drawing Common Ground Through Iterative Multimodal Dialogue

arXiv:2606.01901v1 Announce Type: cross Abstract: We introduce the Image Reconstruction Game, a fully automated benchmark in which a vision-language model issues corrective instructions to an image ge

Agents

Unsupervised Collaborative Domain Adaptation for Driving Scene Parsing

arXiv:2606.01818v1 Announce Type: new Abstract: Reliable driving scene parsing is a fundamental capability for autonomous vehicles operating in open and dynamic driving environments. However, adapting

agentsarxiv-cs-cv

When AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation

arXiv:2602.16763v2 Announce Type: replace Abstract: Artificial intelligence benchmarks are an important mechanism for measuring model progress and guiding deployment decisions. However, benchmarks qui

WorldCoder-Bench: Benchmarking Physically Grounded 3D World Synthesis

arXiv:2606.01869v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly asked not only to write static interfaces, but to construct executable interactive worlds from natural lan

Agents

Before Parc Ferme: RL-Time Pruning for Efficient Embodied LLMs in Autonomous Driving

arXiv:2605.31256v1 Announce Type: new Abstract: Embodied Large Language Models (LLMs) are increasingly used as reasoning modules in robotic control pipelines to improve human-robot interaction, but th

agentsarxiv-cs-ro

BlueFin: Benchmarking LLM Agents on Financial Spreadsheets

arXiv:2605.30907v1 Announce Type: cross Abstract: We present BlueFin, a benchmark that tasks large language model (LLM) agents with synthesis, manipulation, and comprehension tasks over spreadsheet wo

CoFiDA-M: Concept-Aware Feature Modulation for Cross-Domain Adaptation with Image-Only Inference

model-releasesarxiv-cs-cv

arXiv:2605.31591v1 Announce Type: new Abstract: Models for AI-based skin cancer screening suffer a severe performance drop when shifting from expert dermoscopic (source) images to consumer-grade clini

Consolidating Rewarded Perturbations for LLM Post-Training

arXiv:2605.31494v1 Announce Type: new Abstract: Post-training of language models is commonly framed as a sample-score-update loop implemented by gradient descent. A recent line of work, exemplified by

researcharxiv-cs-cl

CSULoRA: Closest Safe Update Low-Rank Adaptation

arXiv:2605.30640v1 Announce Type: cross Abstract: Low-rank adaptation has become a standard method for parameter-efficient fine-tuning of large language models, but even small amounts of unsafe or adv

Effective Reasoning Chains Reduce Intrinsic Dimensionality

arXiv:2602.09276v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) reasoning and its variants have substantially improved the performance of language models on complex reasoning tasks, y

Tutorials

Eigenvectors of Experts are Training-free Non-collapsing Routers

arXiv:2605.30992v1 Announce Type: new Abstract: Sparse Mixture of Experts (SMoE) architectures improve the training efficiency of Large Language Models (LLMs) by routing input tokens to a selected sub

tutorialsarxiv-cs-lg