Search: “framework”

arXiv:2610.19478v1 Announce Type: new Abstract: Agricultural systems make decisions over heterogeneous entity types, textual judgments, and knowledge-question options. Generating a textual answer adds

hardwarearxiv-cs-cl

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

DGX agent

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

model-releasesarxiv-cs-ai

15 Oct 2026

AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric Constraints

arXiv:2512.16245v2 Announce Type: replace Abstract: Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standar

AlignPoison: Conditional Targeted Poisoning of Generative Recommenders via Decoding-Aligned Prefixes

arXiv:2610.14487v1 Announce Type: new Abstract: Generative recommendation models based on autoregressive decoding have been adopted as alternatives to classical ranking-based systems. While their mode

Analyzing the Dynamics of WSBM-based Echo State Networks using InputDSA

arXiv:2610.15380v1 Announce Type: new Abstract: Bridging the structural gap between biological brains and artificial neural networks presents a pathway to altered computational dynamics. This paper in

ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding

model-releasesarxiv-cs-cl

arXiv:2610.16859v2 Announce Type: replace Abstract: For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task mus

AphaVoice: Text-to-Speech Model for Aphasia Patient Simulation

arXiv:2610.14479v1 Announce Type: cross Abstract: While language therapy is the primary treatment for post-stroke aphasia, limited clinical resources often restrict patient access to proper care. Addr

Are Benchmarks Reliable? Toward Structural Diagnosis via Item-Level Capability Boundaries

arXiv:2609.33196v2 Announce Type: replace Abstract: Evaluating large language models (LLMs) relies heavily on benchmark scores, yet aggregate metrics can obscure whether individual items serve their i

Are Multimodal Benchmarks Really Useful? Item-Level Multimodal Benchmark Diagnosis via Structure-Response Co-Calibration

arXiv:2610.14542v1 Announce Type: new Abstract: Multimodal benchmarks are central to evaluating whether models can reason over information from multiple modalities. However, existing literature has re

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models

arXiv:2610.20157v1 Announce Type: new Abstract: World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction. However, task-level ins

researcharxiv-cs-ro

au-Emotion-Bench: Exposing the Interaction Fragility of LLM Agents through Real-World User Emotions

model-releasesarxiv-cs-cl

arXiv:2610.19560v1 Announce Type: cross Abstract: In long-horizon tool-calling tasks, LLM agents can fail not only because of tool-use errors, but also because of ineffective interaction with users. Y

Applications

AutoRSR: Automated Real-to-Sim-to-Real Data Generation for Scalable Robot Learning

arXiv:2610.20336v1 Announce Type: new Abstract: Scaling embodied robot learning requires large and diverse manipulation datasets, but collecting real-world demonstrations remains expensive in human ef

applicationsarxiv-cs-ro

Back on Track: Deployment-time Policy Improvement via World Model Planning

arXiv:2610.19579v1 Announce Type: new Abstract: State-of-the-art visuomotor policies are increasingly capable of executing complex tasks, yet can fail during deployment in ways they cannot predict or

safetyarxiv-cs-ro

Back to the Future: Reverse-Consequence Modeling for Long-Horizon Particle Dynamics

arXiv:2610.18168v1 Announce Type: new Abstract: Accurate prediction of object trajectories is fundamental to mechanical understanding and robotic control. However, autoregressive models inherently suf

Backpropagating Verifier Rewards Through Continuous Flow Language Models

arXiv:2610.19080v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning of autoregressive and discrete-diffusion language models. Language models that gene

safetyarxiv-cs-lg

Benchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints

arXiv:2610.17027v1 Announce Type: new Abstract: Detecting credit card fraud is notoriously difficult because fraudulent charges make up less than 0.2% of total transactions. Quantum Machine Learning (

Beyond Answer Voting: Fine-Grained Correction of LLM Reasoning through Graph Alignment across Sampled Traces

arXiv:2610.18606v1 Announce Type: new Abstract: Large language models increasingly tackle tasks that require multi-step reasoning, where errors in intermediate claims can affect the final answer. Self

Beyond Black Boxes: Visual Grounding for Text Embeddings

arXiv:2610.18047v1 Announce Type: new Abstract: In this paper, our goal is to represent text embeddings as sketches for three main reasons. First, to visualize text representation and to explore their

Beyond DFT electronic band structures via dual-space orbital learning

model-releasesarxiv-cs-lg

arXiv:2610.19919v1 Announce Type: new Abstract: Accurate electronic band structures are essential for predicting material properties, but high-fidelity calculations are computationally demanding. We i

Beyond Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench

model-releasesarxiv-cs-lg

arXiv:2610.18938v1 Announce Type: cross Abstract: Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific co

Beyond Expert Rankings: Contrast Calibration for Mixed-Precision MoE Quantization

arXiv:2610.20353v1 Announce Type: new Abstract: Mixture-of-experts (MoE) language models activate only a few experts per token, yet all expert weights must be stored. Mixed-precision quantization redu

researcharxiv-cs-lg

Beyond Kinematic Tracking: Preserving Expressive Characteristics in Humanoid Whole-Body Control

arXiv:2610.19393v1 Announce Type: new Abstract: Whole-body control plays a crucial role in enabling humanoid robots to execute expressive motions. Faithful execution requires preserving both the inten

safetyarxiv-cs-ro

Beyond Outcome Feedback: Trajectory-Quality-Guided Experience-based Learning

arXiv:2610.14877v1 Announce Type: new Abstract: Experience-based learning enables large language model (LLM) agents to improve over time by reusing knowledge from past executions. However, existing me

Beyond Static Cues: Unified Dynamic Detection of MLLM Backdoors via Dual-Flow Trajectory Analysis

arXiv:2610.20319v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a fo

safetyarxiv-cs-cv

BFHD: Bidirectional Feature Harmonization Decomposition for Heterogeneous Clinical Assessments

arXiv:2610.19352v1 Announce Type: new Abstract: Clinical assessments are often collected using heterogeneous assessment systems across centers and time, leading to records that mix different but relat

researcharxiv-cs-lg

Agents

BLADE: Auditing Information Use for Failure Attribution in LLM Multi-Agent Systems

arXiv:2610.18780v1 Announce Type: new Abstract: Large language model multi-agent systems extend individual agents' capabilities through collaboration across specialized roles, tools, and workflows. Ye

agentsarxiv-cs-ai

Bridging the Topological Divide: Dual-Branch Graph Distillation with Semantic Priors for Robust Cold-Start Recommendation

model-releasesarxiv-cs-lg

arXiv:2610.19578v1 Announce Type: cross Abstract: Graph Collaborative Filtering models have achieved remarkable success in recommendation systems. However, they inherently suffer from a catastrophic r

Bytes to Threats: Byte-Sequence Transformer For Malware Detection

arXiv:2610.18787v1 Announce Type: cross Abstract: Existing malware detection approaches heavily rely on handcrafted features derived from static or dynamic analysis of the executable files. These meth

CARD: Closing the Teacher-Student Loop for Adversarial Robustness Distillation

arXiv:2610.19911v1 Announce Type: cross Abstract: Adversarial robustness distillation typically treats a robust teacher as a fixed knowledge source and transfers robustness to a compact student in a o

researcharxiv-cs-cv

Chain of Thought Monitoring Can Fail Even When CoT Is Necessary

arXiv:2610.18105v1 Announce Type: new Abstract: Chain of Thought (CoT) monitoring is used by frontier labs to detect misbehaviour of AI systems. Yet, its reliability remains poorly understood. We attr

CLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation Objectives

arXiv:2610.16876v1 Announce Type: new Abstract: Target-aware multimodal instruction selection requires useful examples and an appropriate balance of supervision. Sample-level rankings can overrepresen

CockpitHAT: Dependency-Graph-Driven Hierarchical Attribution for Embodied Multi-Agent Cockpits

arXiv:2608.01805v2 Announce Type: replace Abstract: LLM multi-agent systems suffer from Correctness Collapse, where high task-level accuracy conceals severe process-level failures. This is especially

CodecFlow: Efficient Bandwidth Extension via Conditional Flow Matching in Neural Codec Latent Space

arXiv:2603.02022v3 Announce Type: replace-cross Abstract: Speech Bandwidth Extension improves clarity and intelligibility by restoring/inferring appropriate high-frequency content for low-bandwidth sp

Local Ai

CoDy: Codec Dynamics as Complementary Priors for Unsupervised Temporal Action Localization

arXiv:2610.19880v1 Announce Type: new Abstract: Unsupervised temporal action localization (UTAL) aims to identify action categories and localize their temporal boundaries without annotation supervisio

local-aiarxiv-cs-cv

Collective Learning for Unified Robotic Manipulation via Predictive Dynamics Adaptation

arXiv:2610.19141v1 Announce Type: new Abstract: Learning a collective policy for state-based Cartesian manipulation across diverse robotic embodiments presents a fundamental challenge due to embodimen

safetyarxiv-cs-ro

CompanionSafe: From Multi-turn Safety Evaluation to Guardrails for AI Companions

arXiv:2610.18095v1 Announce Type: new Abstract: AI companions provide users with emotional support and ongoing companionship, but their sustained relational interactions also introduce distinct safety

Comparative Evaluation of Deep-Learning based DoA Estimators for Real-Time ISAC Beamforming

arXiv:2610.20326v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) systems rely on accurate Direction-of-Arrival (DoA) estimation for effective beamforming and spectral-effici

researcharxiv-cs-lg

Compare to Correct: Pairwise-Guided Logit Adjustment for LLM Test-Time Scaling

arXiv:2610.18583v1 Announce Type: new Abstract: Sampling-based test-time scaling enhances LLM reasoning by aggregating multiple reasoning paths for the same query. Existing methods use answer frequenc

Comparing Socially-Equitable Renewable Energy Budget Allocation MDP Policies in Mature and Emerging Economies

arXiv:2607.10201v2 Announce Type: replace-cross Abstract: Equitable renewable-energy planning is a sequential decision problem, but the decision variables available to a public planner differ sharply

Applications

Complementary Future Token Pruning for World Action Models

arXiv:2610.19957v1 Announce Type: new Abstract: World action models (WAMs) jointly predict future visual states and robot actions, but processing dense future-frame tokens incurs substantial inference

applicationsarxiv-cs-ro

Computational compressive imaging reconstruction with a simulated-annealing-based Ising solver

arXiv:2610.19778v1 Announce Type: cross Abstract: Computational compressive imaging, such as single-pixel imaging and lensless imaging, is a promising imaging technique, enabling the reconstruction of

researcharxiv-cs-cv

Convex-Analytic View of Query Selection for Safety Verification of Markov Decision Processes

arXiv:2610.17541v1 Announce Type: cross Abstract: Safety verification of a Markov decision process (MDP) asks whether the probabilities of reaching several failure states jointly lie in a convex safe

Correction Training for Diffusion Models

arXiv:2610.14136v2 Announce Type: new Abstract: Iterative sampling in diffusion models can lead to error accumulation due to exposure bias. The denoiser is trained on real images interpolated with noi

Coupled Harness--Model Evolution for Scientific Equation Discovery

arXiv:2610.17740v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to discover scientific equations from experimental data. Such a discovery system has two parts that m

CoWear: Towards Collaborative Wearable Inertial Localization with Multiple Smart Devices

arXiv:2610.20596v1 Announce Type: new Abstract: Consumer smart devices observe the same human motion from different body locations, yet existing inertial-localization benchmarks rarely provide synchro

researcharxiv-cs-ro

Cross-Protocol Personality Assessment with LLMs: Aligning Behavioral Evidence with Human Ratings

arXiv:2610.16050v1 Announce Type: new Abstract: Personality assessment from asynchronous video interviews (AVIs) plays a crucial role in recruitment by enabling standardized and behaviorally grounded

CSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing

model-releasesarxiv-cs-cl

arXiv:2610.20272v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated multilingual capabilities across diverse language generation and understanding tasks. Yet effective code-