Search: “models”

Adversarial Attacks Against MLLMs via Progressive Resolution Processing and Adaptive Feature Alignment

arXiv:2605.09902v1 Announce Type: new Abstract: Adversarial perturbations can mislead Multimodal Large Language Models (MLLMs) recognize a benign image as a specific target object, posing serious risk

safetyarxiv-cs-cv

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Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates

DGX agent

arXiv:2605.09337v1 Announce Type: new Abstract: We propose FAR-SIGN (Fully Asynchronous Robust optimization via SIGNed directional projections) for adversary-resilient learning in parameter-server--wo

model-releasesarxiv-cs-lg

12 May 2026

Agentic MIP Research: Accelerated Constraint Handler Generation

arXiv:2605.09186v1 Announce Type: new Abstract: Mixed-integer programming (MIP) research is both mathematically sophisticated and engineering-intensive: testing an algorithmic hypothesis within a bran

Applications

AI Gateway production index

Vercel's AI Gateway production index is a monitoring tool that tracks the performance and reliability of AI services and models in production environments. It likely provides metrics on latency, uptim

applicationsvercel-blog

AlphaExploitem: Going Beyond the Nash Equilibrium in Poker by Learning to Exploit Suboptimal Play

arXiv:2605.09150v1 Announce Type: new Abstract: Poker is an imperfect information game that has served as a long-standing benchmark for decision-making under uncertainty. To maximize utility beyond th

Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks

arXiv:2605.10590v1 Announce Type: cross Abstract: Causal sensitivity analysis aims to provide bounds for causal effect estimates in the presence of unobserved confounding. However, existing methods fo

researcharxiv-cs-lg

Anthropic announces 12 Claude plugins for the legal sector, including a 'commercial counsel' tool for reviewing vendor agreements and a bar exam study tool (Rachel Metz/Bloomberg)

Rachel Metz / Bloomberg: Anthropic announces 12 Claude plugins for the legal sector, including a “commercial counsel” tool for reviewing vendor agreements and a bar exam study tool — Anthropic PBC is

model-releasestechmeme

Arcane: An Assertion Reduction Framework through Semantic Clustering and MCTS-Guided Rule Exploring

arXiv:2605.10107v1 Announce Type: new Abstract: Assertion-based Verification (ABV) is essential for ensuring that hardware designs conform to their intended specifications. However, existing automated

AssemPlanner: A Multi-Agent Based Task Planning Framework for Flexible Assembly System

model-releasesarxiv-cs-ro

arXiv:2605.08831v1 Announce Type: new Abstract: In flexible assembly systems, existing task planning methods require a time-consuming configuration process by multiple experts to establish a productio

ASTRA-QA: A Benchmark for Abstract Question Answering over Documents

model-releasesarxiv-cs-cl

arXiv:2605.10168v1 Announce Type: new Abstract: Document-based question answering (QA) increasingly includes abstract questions that require synthesizing scattered information from long documents or a

Attractor-Vascular Coupling Theory: Formal Grounding and Empirical Validation for AAMI-Standard Cuffless Blood Pressure Estimation from Smartphone Photoplethysmography

arXiv:2605.10871v1 Announce Type: cross Abstract: This work proposes Attractor-Vascular Coupling Theory (AVCT), a mathematical framework showing that cardiac attractor geometry encodes blood pressure

researcharxiv-cs-ai

Automated Approach for Solving Infinite-state Polynomial Reachability Games

arXiv:2605.10169v1 Announce Type: new Abstract: Reachability games are two-player games played on a graph, where the objective of exttt{REACH} player is to reach the target set whereas the objective o

BabelDOC: Better Layout-Preserving PDF Translation via Intermediate Representation

model-releasesarxiv-cs-cl

arXiv:2605.10845v1 Announce Type: cross Abstract: As global cross-lingual communication intensifies, language barriers in visually rich documents such as PDFs remain a practical bottleneck. Existing d

Agents

Batch-of-Thought: Cross-Instance Learning for Enhanced LLM Reasoning

arXiv:2601.02950v3 Announce Type: replace Abstract: Current Large Language Model reasoning systems process queries independently, discarding valuable cross-instance signals such as shared reasoning pa

agentsarxiv-cs-ai

BCJR-QAT: A Differentiable Relaxation of Trellis-Coded Weight Quantization

arXiv:2605.10655v1 Announce Type: new Abstract: Trellis-coded quantization sets the current 2-bit post-training frontier for LLMs (QTIP), but pushing below the PTQ ceiling requires quantization-aware

Local Ai

Beyond Bag-of-Patches: Learning Global Layout via Textual Supervision for Late-Interaction Visual Document Retrieval

arXiv:2605.08421v1 Announce Type: new Abstract: Visual Document Retrieval (VDR) models mostly rely on late interaction architectures, in which documents are represented by a set of local patch embeddi

local-aiarxiv-cs-cv

Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMs

arXiv:2605.09268v1 Announce Type: cross Abstract: Users interacting with Large Language Models (LLMs) in a multi-turn conversation routinely refine their requests or pivot to new topics. LLMs, however

safetyarxiv-cs-ai

Beyond Hard Writes and Rigid Preservation: Soft Recursive Least-Squares for Lifelong LLM Editing

arXiv:2601.15686v2 Announce Type: replace Abstract: Model editing updates a pre-trained LLM with new facts or rules without retraining while preserving unrelated behavior. In real deployment, edits ar

researcharxiv-cs-lg

Beyond Isolation: A Unified Benchmark for General-Purpose Navigation

model-releasesarxiv-cs-ro

arXiv:2605.09441v1 Announce Type: new Abstract: The pursuit of general-purpose embodied agents is hindered by fragmented evaluation protocols that isolate navigation skills and fixate on specific robo

Beyond Position Bias: Shifting Context Compression from Position-Driven to Semantic-Driven

arXiv:2605.09463v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated exceptional performance across diverse tasks. However, their deployment in long-context scenarios faces h

safetyarxiv-cs-cl

Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning

arXiv:2605.08271v1 Announce Type: cross Abstract: Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For

Bridging Spectral Operator Learning and U-Net Hierarchies: SpectraNet for Stable Autoregressive PDE Surrogates

arXiv:2605.09096v1 Announce Type: new Abstract: Neural operators for time-dependent PDEs face a structural tension: spectral architectures (FNO and descendants) inherit exponential rollout-error growt

bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition

arXiv:2605.10661v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are built by stacking independently parameterized blocks, but it remains unclear how much of this depth requires layer spec

Calibrate, Don't Curate: Label-Efficient Estimation from Noisy LLM Judges

arXiv:2605.09702v1 Announce Type: cross Abstract: Multi-judge evaluation is increasingly used to assess LLMs and reward models, and the prevailing heuristic is to curate: keep the most accurate judges

researcharxiv-cs-cl

Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation

arXiv:2605.10448v1 Announce Type: new Abstract: Interactive agent benchmarks map an agent run to a binary outcome through outcome checks. When these checks rely on surface level signals or fail to cap

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key

arXiv:2605.06638v2 Announce Type: replace Abstract: Reinforcement learning (RL) has been applied to improve large language model (LLM) reasoning, yet the systematic study of how training scales with t

researcharxiv-cs-ai

Applications

CASISR: Circular Arbitrary-Scale Image Super-Resolution

arXiv:2605.08173v1 Announce Type: new Abstract: The generalization performance (GP) of deep learning-based arbitrary-scale image super-resolution (ASISR) methods is subject to limited training dataset

applicationsarxiv-cs-cv

CATS: Curvature Aware Temporal Selection for efficient long video understanding

arXiv:2605.09223v1 Announce Type: new Abstract: Understanding long videos with multimodal large language models (MLLMs) requires selecting a small subset of informative frames under strict computation

researcharxiv-cs-cv

Causal Explanations from the Geometric Properties of ReLU Neural Networks

arXiv:2605.10396v1 Announce Type: new Abstract: Neural networks have proved an effective means of learning control policies for autonomous systems, but these learned policies are difficult to understa

safetyarxiv-cs-lg

Tutorials

CausalGS: Learning Physical Causality of 3D Dynamic Scenes with Gaussian Representations

arXiv:2605.10586v1 Announce Type: new Abstract: Learning a physical model from video data that can comprehend physical laws and predict the future trajectories of objects is a formidable challenge in

tutorialsarxiv-cs-cv

Tutorials

CauSim: Scaling Causal Reasoning with Increasingly Complex Causal Simulators

arXiv:2605.09079v1 Announce Type: new Abstract: Despite surpassing human performance across mathematics, coding, and other knowledge-intensive tasks, large language models (LLMs) continue to struggle

tutorialsarxiv-cs-ai

Cavity-Enhanced Collective Quantum Processing with Polarization-Encoded Qubits

arXiv:2605.10473v1 Announce Type: cross Abstract: We introduce a cavity-enhanced optical architecture for collective quantum processing in which logical qubits are encoded in the polarization subspace

Tutorials

Central Limit Theorem for Two-Time-Scale Approximate Distributionally Robust RL

arXiv:2605.08417v1 Announce Type: new Abstract: Designing model-free algorithms for distributionally robust reinforcement learning (DRRL) poses fundamental challenges. The robust Bellman operator is n

tutorialsarxiv-cs-lg

ChaosNetBench: Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamics

arXiv:2605.09676v1 Announce Type: cross Abstract: Spatio-temporal graph neural networks (STGNNs) are widely used for short-term forecasting in dynamic physical systems such as traffic and weather. How

Cheap Thrills: Effective Amortized Optimization Using Inexpensive Labels

arXiv:2603.05495v2 Announce Type: replace Abstract: To scale optimization and simulation, prior work has explored training machine-learning surrogates that map problem parameters to solutions inexpens

researcharxiv-cs-lg

Chinese Cyberbullying Detection: Dataset, Method, and Validation

arXiv:2505.20654v2 Announce Type: replace-cross Abstract: Existing cyberbullying detection benchmarks were organized by the polarity of speech, such as 'offensive' and 'non-offensive', which were esse

Local Ai

Chroma1-HD Character Transfer with Flux.2 Dev

local-air-stablediffusion

Chroma1-HD is an 8.9B parameter text-to-image foundational model based on FLUX.1-schnell , ideal for finetuning on specific styles, concepts, or characters . The Reddit discussion likely covers techni

CIVeX: Causal Intervention Verification for Language Agents

arXiv:2605.09168v1 Announce Type: new Abstract: A valid tool call is not necessarily a valid intervention. Tool-using language agents are guarded by schema validators, policy filters, provenance check

🤩🤯🤩 Claude Code (still not AGI but biggest advance since GPT-4) is the most neurosymbolic thing I have ever seen in my life. 53 symbolic …

model-releasesgary-marcus--x

🤩🤯🤩 Claude Code (still not AGI but biggest advance since GPT-4) is the most neurosymbolic thing I have ever seen in my life. 53 symbolic tools, 500,000 lines of symbolic code, combined with a state-of

Claude Opus 4.7 (fast mode) is now available in Windsurf! Full Claude Opus 4.7 intelligence ~2.5x higher output speeds We can't wait to see …

model-releaseswindsurf--x

Windsurf has released Claude Opus 4.7 in fast mode, offering the full intelligence of Claude Opus 4.7 with approximately 2.5x faster output speeds. This integration allows users of Windsurf to access

Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectories

arXiv:2605.10840v1 Announce Type: cross Abstract: We present Clin-JEPA, a multi-phase co-training framework for joint-embedding predictive (JEPA) pretraining on EHR patient trajectories. JEPA architec

CoLA-Flow Policy: Temporally Coherent Imitation Learning via Continuous Latent Action Flow Matching for Robotic Manipulation

arXiv:2601.23087v3 Announce Type: replace Abstract: Learning long-horizon robotic manipulation requires jointly achieving expressive behavior modeling, real-time inference, and stable execution, which

safetyarxiv-cs-ro

Communication Dynamics Neural Networks: FFT-Diagonalized Layers for Improved Hessian Conditioning at Reduced Parameter Count

arXiv:2605.08171v1 Announce Type: cross Abstract: Background and motivation. The Communication Dynamics (CD) framework, introduced in two earlier papers for atomic-energy prediction and field-induced

Complex-Valued Phase-Coherent Transformer

arXiv:2605.10123v1 Announce Type: new Abstract: Complex-valued Transformers have largely inherited softmax attention from real-valued architectures. However, row-normalised token competition is not ne

Compressed Video Aggregator: Content-driven Module for Efficient Micro-Video Recommendation

arXiv:2605.08810v1 Announce Type: cross Abstract: We propose Compressed Video Aggregator (CVA), a lightweight micro-video recommendation module that decouples video information from preference learnin

ConFit v3: Improving Resume-Job Matching with LLM-based Re-Ranking

model-releasesarxiv-cs-cl

arXiv:2605.09760v1 Announce Type: new Abstract: A reliable resume-job matching system helps a company find suitable candidates from a pool of resumes and helps a job seeker find relevant jobs from a l

Conformity Generates Collective Misalignment in AI Agents Societies

arXiv:2605.10721v1 Announce Type: cross Abstract: Artificial intelligence safety research focuses on aligning individual language models with human values, yet deployed AI systems increasingly operate

safetyarxiv-cs-cl

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization

arXiv:2602.05902v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) enables efficient deployment of large language models by mapping pretrained weights to low-bit formats withou

researcharxiv-cs-ai