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Bridging Reinforcement Learning and Optimal Control via Feasible Action Mapping

model-releasesarxiv-cs-ro

arXiv:2607.23930v1 Announce Type: cross Abstract: Operating constrained dynamical systems requires controllers to efficiently solve complex tasks while enforcing recursive feasibility and safety const

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Model Releases

CachedSearch: Training-Free Cached Exploration for Test-Time Search in Video Diffusion

DGX agent

arXiv:2607.23159v1 Announce Type: new Abstract: Test-time search lets small video diffusion models rival larger ones, but costs 2-10x more. All candidates are fully denoised, although most are discard

model-releasesarxiv-cs-ai

28 Jul 2026

CallBench: A Benchmark for Dual-Goal Coordination in Phone Call Assistants

arXiv:2607.22635v1 Announce Type: new Abstract: Target-oriented dialogue systems have demonstrated strong capabilities in completing user goals through interactive conversations. However, existing stu

CALMRec: Causally Aligned Language Memory for Long-Horizon Recommendation

arXiv:2607.23647v1 Announce Type: cross Abstract: Large language models (LLMs) can summarize heterogeneous user evidence in natural language, but current LLM recommenders often collapse enduring prefe

CameraAnything: Refilming Videos with Arbitrary Camera Control

arXiv:2607.24591v1 Announce Type: new Abstract: We introduce CameraAnything, the first unified framework for camera controlled video editing that enables joint control of both intrinsic and extrinsic

Can Context Bridge the Reality Gap? Sim-to-Real Transfer of Context-Aware Policies

model-releasesarxiv-cs-ro

arXiv:2511.04249v2 Announce Type: replace Abstract: Sim-to-real transfer remains a major challenge in reinforcement learning (RL) for robotics, as policies trained in simulation often fail to generali

CausalGate: Causal Importance Distillation for Transformer Module Pruning

model-releasesarxiv-cs-cl

arXiv:2607.22720v1 Announce Type: cross Abstract: Existing adaptive inference methods for Large Language Models rely on observational heuristics, such as hidden-state similarity or activation magnitud

CC-AOS: Cost- and Horizon-Conditioned Amortized Backward Induction for Finite-Horizon Optimal Stopping

arXiv:2607.22774v1 Announce Type: new Abstract: Finite-horizon optimal stopping is a central problem in early time-series classification, where a system must decide at each sequence prefix whether the

Chamaileon: Cross-Context Binder Design with Contextualized Modeling and Mixed Sampling

arXiv:2607.23518v1 Announce Type: new Abstract: The rapid evolution of generative models has unlocked new potentials in protein binder design, a pivotal task in structural biology, by facilitating end

Chart Deception in Vision-Language Models: From Vulnerability to Mitigation

arXiv:2607.22600v1 Announce Type: new Abstract: Information visualizations are widely used to communicate patterns, trends, and outliers, yet deceptive design choices-such as truncated or inverted axe

Cheap Probes Predict Expensive Training in 3D-CT Vision--Language Models

arXiv:2607.22771v1 Announce Type: cross Abstract: Picking the frozen image encoder for a 3D~CT vision--language model (VLM), together with the token-compression scheme on top of it, is a search over m

Child-Oriented AIGC Video Risk Reviewing: A Benchmark and Knowledge-Supported Iterative Reasoning Framework

arXiv:2607.22715v1 Announce Type: new Abstract: The rapid growth of Artificial Intelligence-generated content (AIGC) is reshaping video production and circulation, exposing children to an increasing v

Choosing a Text Embedding Model: A Practical Benchmarking and Decision Framework

arXiv:2607.23507v1 Announce Type: cross Abstract: Choosing the right text embedding model is one of the most consequential -- and most frequently under-examined -- decisions in building a retrieval or

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

arXiv:2607.24743v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundam

Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs

arXiv:2607.24371v1 Announce Type: cross Abstract: Healthcare interoperability requires AI systems to produce structured outputs conforming to standardized schemas including ICD-10 for diagnostic codin

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs

arXiv:2607.22577v1 Announce Type: new Abstract: Scaling large language models (LLMs) has driven their success, yet dense Transformers couple capacity and computation: every parameter is activated for

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

arXiv:2607.23089v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled automated kernel generation and optimization, but most existing approaches rely on surface

Compressing LLMs with MoP: Mixture of Pruners

arXiv:2602.06127v2 Announce Type: replace Abstract: The high computational demands of Large Language Models (LLMs) motivate methods that reduce parameter count and accelerate inference. In response, m

Confidently Wrong: Exception Chain Collapse in Frontier LLM Rule Evaluation

arXiv:2607.23386v1 Announce Type: new Abstract: We document a failure class in frontier large language models -- exception chain collapse -- observed in eligibility evaluation under nested conditional

ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control

arXiv:2607.22962v1 Announce Type: new Abstract: LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning. A hallucinated

Consistent Evidence, Robust Recognition: Faithful Attribution Regularization under Geometric Transformations

arXiv:2607.23835v1 Announce Type: new Abstract: Attribution methods are widely used to characterize the evidence underlying model predictions, yet their potential to improve model behavior remains und

Constraint-Bound Agnostic Bayesian Optimization: One Model for All Thresholds

arXiv:2607.23448v1 Announce Type: cross Abstract: Expensive constrained optimization problems in real-world industry design often involve constraint thresholds that are difficult to determine in advan

Context-Adaptive Inference: A Unified Statistical and Foundation-Model View

arXiv:2607.23304v1 Announce Type: cross Abstract: Modern predictive systems are expected to adapt their behavior to the specific situation they are facing. A clinical model should not treat every pati

Context Is King: How In-Context Specification Shapes the Geometry of Concepts

arXiv:2607.24425v1 Announce Type: new Abstract: Large language models place structured concepts on geometrically faithful manifolds: weekdays lie on a circle, months on another, usually taken to be a

Continual Knowledge Consolidation LORA for Domain Incremental Learning

arXiv:2510.16077v2 Announce Type: replace-cross Abstract: Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without c

Contrastive Parameter Disentanglement for Multi-modal Remote Sensing Image Generation

arXiv:2607.23673v1 Announce Type: new Abstract: Existing remote sensing image generation methods are largely confined to single-modality synthesis and therefore fail to exploit the complementary infor

Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation

arXiv:2607.23860v1 Announce Type: cross Abstract: Deep ensembles provide the most reliable uncertainty estimates in deep learning, but their cost grows linearly with the number of members. Implicit en

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607.22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents aut

Cortex: Compact Behavior Cloning for Quake with Frozen Visual Features

arXiv:2607.22739v1 Announce Type: cross Abstract: We study how far a deliberately simple behavioral-cloning policy can progress in a visually rich first-person game before adding reinforcement learnin

Cost-Aware Recovery-Pathway Identification and Bayesian Optimization for Autonomous Materials Discovery

arXiv:2607.23896v1 Announce Type: new Abstract: Autonomous laboratories automate experimental execution, but a campaign must also decide which recovery pathway merits optimization. We formulate this a

D-Score: A Spectral Hidden-State Signal for Hallucination Detection in Large Language Models

arXiv:2607.24586v1 Announce Type: cross Abstract: Large Language Models can produce fluent text that is false, unsupported by the available evidence, or inconsistent with information that appears to b

DailyBench: A Unified Benchmark for AI-Generated and Manipulated Images from Modern Generative Models

arXiv:2607.24016v1 Announce Type: new Abstract: Recent advances in generative models have shifted AI-generated image detection from identifying easily distinguishable, fully synthetic images to identi

DAMamba-UNet3D: A Parameter-Efficient Mamba State Space U-Net with Dynamic Adaptive Scan for 3D Medical Image Segmentation

arXiv:2607.22718v1 Announce Type: cross Abstract: We propose parameter-efficient SSM-based U-Net architectures for 3D medical image segmentation. Convolutional U-Nets afford O(n) local mixing per laye

DAP-Pose: Deep Temporal Alignment and Physics-aware Cross-modal Sensor Fusion for Robust Pose Estimation

arXiv:2607.23755v1 Announce Type: new Abstract: Robust and accurate pose estimation with multi-modal sensors is fundamental for autonomous vehicles and mobile robotic systems in complex environments.

Decentralized Granular Access Control for Agentic AI Systems in Critical Infrastructure

arXiv:2607.22611v1 Announce Type: new Abstract: The deployment of autonomous AI agents in production infrastructure introduces fundamental security challenges that traditional role-based access contro

DeepLens Diagnosis Agent: Agentic Workflow Design Lets a Small Reasoning Model Compete with Frontier LLMs

arXiv:2607.22555v1 Announce Type: new Abstract: Medical diagnosis is a multi-stage process: extract facts, consult knowledge, generate a differential analysis, and select the best diagnosis with expla

DeepLook: Deeper Thinking with Lookahead

arXiv:2607.22602v1 Announce Type: new Abstract: Inference-time scaling has emerged as a powerful paradigm for improving large language model reasoning, often delivering larger gains on difficult reaso

Design Theater: A Benchmark for Generative UI

arXiv:2607.22928v1 Announce Type: new Abstract: Generative UI tools promise to democratize UI design by turning natural language descriptions into complete interfaces. Alongside the interface, these t

Diffusion-Guided Search via Exponential Tilting (DiffTilt): An Application to Falsification of Safety-Critical Systems

arXiv:2607.23134v1 Announce Type: new Abstract: Discovering rare safety-critical failures in autonomous and cyber-physical systems is a fundamental challenge in verification and validation. Existing f

DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decoding

arXiv:2607.23070v1 Announce Type: new Abstract: Food segmentation is essential for applications such as intelligent catering, dietary assessment, and recommendation. However, existing benchmarks fail

Do Current Retrievers Cover All the Evidence? A Controlled Study of Conjunctive Cross-Page Retrieval

model-releasesarxiv-cs-cl

arXiv:2607.24165v1 Announce Type: cross Abstract: Finding a long document relevant to a multi-part request is not the same as establishing that it contains every requested piece of evidence. We study

Do Diagrams Help Large Language Models Reason? Evidence from Syllogistic Reasoning

arXiv:2607.23513v1 Announce Type: cross Abstract: Diagrams are widely used to support logical reasoning, and prior studies suggest that representations such as Euler diagrams can improve human reasoni

Do Language Models Converge to Themselves? Recursive Self-Refinement as Textual Relaxation

arXiv:2607.22653v1 Announce Type: new Abstract: Large language models are increasingly used in recursive refinement workflows, where an initial draft is repeatedly revised by the same model. Despite t

Do LLMs Know Their Vulnerable Scenarios?

arXiv:2607.23496v1 Announce Type: new Abstract: Safety-aligned large language models are trained to refuse harmful requests, yet embedding the same requests in particular scenarios can bypass their sa

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification

arXiv:2607.22644v1 Announce Type: new Abstract: Real-world document classification pipelines typically apply the same sequence of models to every incoming document, regardless of its complexity or typ

Domain-Prior-Regularized Graph Modeling for Anomaly Detection in Cyber-Physical Systems

arXiv:2607.23197v1 Announce Type: new Abstract: Anomaly detection on multivariate sensor time series is critical for industrial monitoring of cyber-physical systems (CPS), where even subtle deviations

DOSA: A Tree-Guided, Self-Regressive Framework for Long Document Structure Analysis

arXiv:2607.22679v1 Announce Type: new Abstract: In visually-rich documents, information is encoded not only in individual page objects such as tables, headers, and text blocks, but also in the structu

DraftExpert: Expansion-Aware Self-Speculative Decoding for End-Device MoE Inference

arXiv:2607.24434v1 Announce Type: cross Abstract: Large Mixture-of-Experts (MoE) language models are attractive for end-device deployment because only a small subset of experts is active per token, bu