Search: “framework”

Mind Which Bird You Favour: Parameterizing Adequacy-Fluency Balance in Meta-Evaluation of Machine Translation

arXiv:2609.14795v1 Announce Type: cross Abstract: There is a tradeoff in machine translation meta-evaluation between prioritizing alignment with adequacy versus fluency. The balance depends on the com

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Model Releases

Mind2Cloud: EEG-to-Point Cloud Generation with Two-Granularity Diffusion Decoding

DGX agent

arXiv:2609.13991v1 Announce Type: new Abstract: Reconstructing 3D objects from brain signals offers a promising avenue for understanding human visual cognition. While prior work has shown initial succ

model-releasesarxiv-cs-cv

15 Sept 2026

Mind2Dialogue: Training Human-Aware Language Models by Simulating User Mental States

model-releasesarxiv-cs-cl

arXiv:2609.15972v1 Announce Type: new Abstract: As language models become more capable, long-term collaboration in learning, reasoning, and decision-making calls for a deeper understanding of the peop

Mirror, Mirror on the Wall: Prompt Echoing in Small Instruct Language Models

arXiv:2609.15045v1 Announce Type: cross Abstract: Prompt echoing is a recognized failure mode of instruct language models, in which a model instead of generating a response, mirrors the provided promp

Agents

Modeling Social Dynamics with an LLM-Enabled Agent Based Network-Dynamic (LAND) Model

arXiv:2608.00929v2 Announce Type: replace Abstract: Social dynamics encode the process in which individual network and discourse interactions aggregate into collective influence, narrative dominance a

agentsarxiv-cs-ai

ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement

model-releasesarxiv-cs-cl

arXiv:2609.14857v1 Announce Type: new Abstract: Recent work extends recursive self-improvement (RSI) to agent harnesses for long-horizon coding and terminal tasks, enabling agents to improve execution

Agents

Moral Rebel Agents: Decision-Making Under Conflicting Obligations

arXiv:2609.14716v1 Announce Type: new Abstract: Autonomous agents are typically obliged to follow user-assigned tasks. However, strict obedience may conflict with moral obligations that arise during e

agentsarxiv-cs-ai

MorphoStyle: Motion Style Transfer with Morphology Control

arXiv:2609.14189v1 Announce Type: new Abstract: Human motion may be viewed as a combination of action content, style, and body morphology. Existing motion style transfer methods transfer a reference s

Applications

MoVT: Video-Augmented Motion Tokenizer for Text-to-Motion Generation

arXiv:2609.14965v1 Announce Type: new Abstract: Text-driven 3D human motion generation models face significant challenges in responding to diverse and unconstrained textual prompts, primarily due to t

applicationsarxiv-cs-cv

N^2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion

arXiv:2506.04166v3 Announce Type: replace Abstract: Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretic

Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Window

arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and ex

NeuroProlog: Multi-Task Fine-Tuning for Neurosymbolic Mathematical Reasoning via the Cocktail Effect

arXiv:2603.02504v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance on natural language tasks but remain unreliable in mathematical reasoning, frequently genera

New Conditions for Philosophers to Catch the Wave of Citizen Deliberation in the Age of Artificial Intelligence in advance

arXiv:2609.15707v1 Announce Type: new Abstract: Powerful technologies labeled ``AI''-without sufficient epistemic caution-are already reshaping political and private life, bringing both new dangers an

Newton Deep Unfolding for Compressed Sensing

arXiv:2609.14391v1 Announce Type: new Abstract: Compressed sensing (CS) reconstructs images from highly limited measurements, but existing deep unfolding methods are typically driven by first-order op

Nonparametric Variance-Penalized Actor-Critic: Statistical Inference for Risk-Sensitive Reinforcement Learning

arXiv:2609.14327v1 Announce Type: new Abstract: Variance penalization is a principled approach to risk-sensitive reinforcement learning (RL) that explicitly trades expected return for policy stability

safetyarxiv-cs-lg

Not All Prompts Are Equal: Exploration-Guided Prompt Scaffolding for Multimodal Reinforcement Post-Training

arXiv:2609.15051v1 Announce Type: cross Abstract: Training prompts in online reinforcement learning (RL) differ substantially in how informative they are for the current policy: some are already satur

Novel Ex-vivo Calf Brain Model with Integrated Sub-Skull Force Sensors to Access Simulated Neurosurgical Procedures

arXiv:2609.14198v1 Announce Type: new Abstract: Surgical tissue manipulation demands precision; however, tool-tissue manipulation force magnitudes under realistic conditions are rarely quantified. To

researcharxiv-cs-ro

One Spectrum, Two Resources: Data-Memory Scaling in Autoregressive Prediction

arXiv:2609.13500v1 Announce Type: cross Abstract: How much learned memory is needed to benefit from more data? We show that the two resources are governed by one predictive-energy spectrum in a positi

researcharxiv-cs-ai

Online Language Adaptive Sampling for Better Distributed Cross-lingual Gains

arXiv:2609.14969v1 Announce Type: cross Abstract: Realignment is a promising approach for improving the cross-lingual transfer ability of multilingual language models, particularly for extremely low-r

Optimizing Sparse Outcomes Through Dense Behavioral Signals via Value-Guided Preference Distillation

arXiv:2609.14648v1 Announce Type: new Abstract: Aligning multi-turn dialogue agents is usually framed as matching turn-level human preferences, yet direct optimization of long-term outcomes is often i

safetyarxiv-cs-cl

Hardware

OpWeave: Flexible Operator Disaggregation for Heterogeneous LLM Serving

arXiv:2609.14237v1 Announce Type: cross Abstract: LLM serving systems increasingly disaggregate inference into finer-grained stages, with recent approaches separating attention from FFN or MoE executi

hardwarearxiv-cs-ai

Agents

OrchSLM: Probing the Dynamics of Small Language Model Orchestration

arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challeng

agentsarxiv-cs-ai

PACE: Progressive Angular-to-Norm Contrastive Embedding

arXiv:2609.15152v1 Announce Type: cross Abstract: Multimodal embedding models encode heterogeneous inputs into a shared embedding space, enabling efficient similarity computation across modalities and

Hardware

Partition-Aware Scheduling for Mobile Heterogeneous Inference Co-Execution

arXiv:2609.14213v1 Announce Type: cross Abstract: Modern mobile inference runs on heterogeneous platforms combining mobile GPUs with multiple CPU core clusters. Existing optimizations typically exploi

hardwarearxiv-cs-lg

PC^2-AD: Point Cloud Upsampling to Safeguard 3D Anomaly Detection with Resolution-constrained Edge Devices

arXiv:2609.14722v1 Announce Type: new Abstract: Low-cost and low-resolution sensors used in edge deployments can produce test point clouds that are substantially sparser than the normal training data.

Perceive, Refine, Reason: A Calibrated Pipeline for Measuring Indicators in Strategic Visual Communication on Social Media

arXiv:2609.14699v1 Announce Type: new Abstract: Visual content shapes audience perception and opinion on social media, and computational social science increasingly relies on automated tools to analyz

Applications

Phorecaster365: A Human-Supervised Reference Architecture for Hybrid Pharmaceutical Sales Forecasting and Planning Decision Support

arXiv:2609.13907v1 Announce Type: cross Abstract: Pharmaceutical sales forecasts inform planning across products, regions, and distribution channels, yet their interpretation depends on inventory avai

applicationsarxiv-cs-ai

PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models

arXiv:2609.14973v1 Announce Type: new Abstract: We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the ph

PhysMent: An Interactive Approach For LLM Reasoning In Physics Problems

model-releasesarxiv-cs-cl

arXiv:2609.13152v1 Announce Type: new Abstract: Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experime

PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection

arXiv:2609.15562v1 Announce Type: cross Abstract: As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploit

Pixel-wise Planarity for High-Precision Monocular Plane Segmentation

arXiv:2609.13246v1 Announce Type: new Abstract: Plane segmentation from a single RGB image remains challenging due to imprecise region grouping and geometrically inconsistent supervision, often leadin

Predictive audio representations for early detection and tracking of hidden dynamic objects

arXiv:2609.13595v1 Announce Type: cross Abstract: Predicting potential dangers is core to safety. Forecasting the presence of other traffic agents is core to danger prediction. Occluded traffic agents

Predictive Likelihood Ratios for Language Model Watermark Detection

arXiv:2609.15657v1 Announce Type: cross Abstract: Keyed watermark detection tests dependence between observed tokens and pseudorandom variables reconstructed from a secret key. Building on the pivotal

researcharxiv-cs-ai

PredTac: Learning Contact-Rich Manipulation with Predicted Touch

arXiv:2609.15198v1 Announce Type: new Abstract: Contact-rich manipulation benefits from tactile feedback, yet physical tactile sensors introduce hardware, calibration, synchronization, and maintenance

safetyarxiv-cs-ro

Principal-timestep Restricted Init via Sparse Matrix-decomposition in Flow-matching

arXiv:2609.15643v1 Announce Type: new Abstract: Flow-matching diffusion models have recently emerged as a strong paradigm for high-fidelity visual generation. However, their prohibitively high fine-tu

safetyarxiv-cs-lg

PRISM-UDE: Physics-Regularized Iterative Symbolic Modeling of 3nm FinFETs via Universal Differential Equation

arXiv:2609.13200v1 Announce Type: cross Abstract: Compact transistor models are the mathematical backbone of circuit simulation. However, at advanced nodes such as 3nm, transport physics becomes too c

Applications

ProtoGuide: Prototype-Driven Guidance for Class-Conditional Graph Generation

arXiv:2609.15239v1 Announce Type: cross Abstract: Discrete diffusion models are a prominent family for graph generation, but standard class-conditional mechanisms embed the class signal in the denoise

applicationsarxiv-cs-ai

Proving olympiad geometry theorems on a superconducting quantum processor

arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang

researcharxiv-cs-ai

PuzzleMate: Benchmarking MLLMs for Egocentric Puzzle Assistance

arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a

QSTAR: Quantum Selective Transfer with Adaptive Routing

arXiv:2607.21411v1 Announce Type: cross Abstract: Quantum transfer learning (QTL) is often evaluated by replacing a classical classifier with a fixed variational quantum head, but this hides a key que

Rank-Consistent Set Reasoning for Co-Salient Object Detection

arXiv:2609.13706v1 Announce Type: new Abstract: Co-salient object detection (Co-SOD) requires a model to find foreground regions that are salient in individual images and supported by the image group.

Reason What Matters: Retrieval-Grounded Reasoning for Universal Multimodal Embeddings

arXiv:2609.15296v1 Announce Type: new Abstract: Universal multimodal embedding (UME) learns unified representations across modalities, enabling a single model to support diverse retrieval tasks. Recen

Reconstructing Is Not Acting: Action-Centric Latent Dynamics Modeling

arXiv:2609.15189v1 Announce Type: new Abstract: Latent action models (LAMs) learn action representations from unlabeled videos by inferring latent actions from visual transitions and reconstructing fu

Refinement-based Flow Policy Optimization

arXiv:2609.15123v1 Announce Type: cross Abstract: Flow-based policies offer an expressive representation for online reinforcement learning, but conventional flow matching requires samples drawn from t

ReH-FUSE: Reliability-Aware Hierarchical Fusion of Experts for Multimodal Emotion Recognition in Conversation

arXiv:2609.13857v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (ERC) requires adapting to the instance-dependent reliability of different evidence sources. Lexical cont

researcharxiv-cs-lg

Reliable Egocentric Action Anticipation via Temporal Reliability Suppression and Compositional Graph Decoding

arXiv:2609.13293v1 Announce Type: new Abstract: Wearable action anticipation systems must remain reliable despite missing frames, masking, and sensor noise, yet existing egocentric anticipation method

Tutorials

ReMemNav: Memory-Based Decision Correction and Target Verification for Zero-Shot Object Navigation

arXiv:2603.26788v3 Announce Type: replace-cross Abstract: Zero-shot object navigation requires agents to locate unseen targets in unfamiliar environments without prior maps or task-specific training.

tutorialsarxiv-cs-cv

Resolution-Independent Analysis of Encoder--Decoder Operator Learning via Limiting Kernels

arXiv:2609.13798v1 Announce Type: cross Abstract: Operator learning is formulated on function spaces, but training data are typically available only through finite-dimensional representations. In enco