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Beyond Sparse Rewards: A New Benchmark and Structure-Aware Graph Alignment for Micro-Drama Understanding

arXiv:2609.07107v1 Announce Type: new Abstract: Micro-dramas, characterized by ultra-short durations and hyper-dense storylines, pose unique challenges for video understanding that conventional benchm

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Beyond Top-k Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents

DGX agent

arXiv:2609.05824v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external skills, but routing user requests over large skill registries is difficult because many

model-releasesarxiv-cs-ai

10 Sept 2026

Beyond Top Words: MonoTM for Topic Modeling with Interpretable Monosemantic Features

arXiv:2609.09575v1 Announce Type: new Abstract: Topic models summarize large text corpora, but top-ranked words often provide only a limited representation of topic semantics. Sparse autoencoders (SAE

Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervised Water Segmentation in High-Resolution Multispectral Imagery

arXiv:2609.10371v1 Announce Type: new Abstract: High-resolution water mapping supports environmental monitoring and related applications, but accurate pixel-level labels are difficult and costly to pr

researcharxiv-cs-cv

Bilevel Planning with Learned Symbolic Abstractions from Interaction Data

arXiv:2603.08599v2 Announce Type: replace Abstract: Intelligent agents must reason over both continuous dynamics and discrete representations to generate effective plans in complex environments. Previ

researcharxiv-cs-ro

BIO-MEMART: Biometric-Aware KV Cache Memory for Multi-User LLM Agents

arXiv:2609.08566v1 Announce Type: new Abstract: KV cache is evolving from a serving optimization into an external memory substrate for long-term LLM agents. In a shared multi-user deployment, however,

researcharxiv-cs-ai

BRACE: Anchored Bellman-Residual Correction for Stale Critics in Asynchronous RL

arXiv:2609.09783v1 Announce Type: new Abstract: Asynchronous reinforcement learning has become the standard way to scale training for language models, but the resulting policy lag biases the critic to

safetyarxiv-cs-lg

Tutorials

BrainTaskonomy: Learning How to Pretrain and What to Transfer in fMRI Foundation Models

arXiv:2609.10518v1 Announce Type: new Abstract: fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are com

tutorialsarxiv-cs-cv

Bridging the Semantic-Utility Gap in Multimodal RAG via Generator-in-the-Loop Alignment

arXiv:2609.08188v1 Announce Type: new Abstract: Vision-language models (VLMs) augmented with retrieval-augmented generation (RAG) benefit from access to external evidence. However, standard retrievers

safetyarxiv-cs-ai

Bridging Theory and Data: Correcting Nuclear Mass Models with Interpretable Machine Learning

arXiv:2603.15203v1 Announce Type: cross Abstract: Nuclear mass prediction is one of the core issues in nuclear physics research, yet it faces the challenge of small-sample datasets with high complexit

BTBR: A Bayesian-Theory-Driven Probabilistic-Fuzzy Framework for Implicit Bias Removal in Large Language Models

arXiv:2408.10608v2 Announce Type: replace Abstract: Large language models (LLMs) may encode biased associations from heterogeneous training corpora that are not immediately visible under ordinary prom

safetyarxiv-cs-cl

Tutorials

Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning

arXiv:2609.10445v1 Announce Type: new Abstract: Reasoning language models have made substantial advances on a variety of complex tasks, yet their capabilities remain overwhelmingly English-centric: mo

tutorialsarxiv-cs-cl

Building the Harness Automatically: Self-Play in Code Distills a Text Harness for Black-Box Optimization

model-releasesarxiv-cs-lg

arXiv:2609.09468v1 Announce Type: new Abstract: Can an agent learn a numerical search strategy through executable practice and then transfer that strategy as text? We study low-budget black-box optimi

Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Construction

arXiv:2609.06391v1 Announce Type: new Abstract: Graph-agentic retrieval-augmented generation combines structured evidence with adaptive controllers that can plan retrieval, traverse relations, verify

agentsarxiv-cs-ai

BuzzASR: A Swarm of 100+ Monolingual Speech Recognition Models

arXiv:2609.09554v1 Announce Type: new Abstract: We introduce BuzzASR, a collection of language-specialized fine-tuned Whisper models adapted for automatic speech recognition (ASR) in 102 languages. La

agentsarxiv-cs-cl

Can Artificial Intelligence Support Healthcare and Mental Health Through Early Cyberbullying Detection ? The Impact of Emotion-Aware AI on Proactive Online Safety

arXiv:2609.09735v1 Announce Type: cross Abstract: Healthcare systems, mental health, and public well-being are increasingly affected by cyberbullying and harmful online interactions. This paper presen

Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization

arXiv:2609.10410v1 Announce Type: new Abstract: The growing complexity of content moderation policies presents a critical challenge for their consistent operationalization. While foundation models pos

Can We Trust Video Hallucination Detectors? VidHalLoc for Evaluating the Evaluators

model-releasesarxiv-cs-cv

arXiv:2609.09895v1 Announce Type: new Abstract: Video-language models and video agents can produce hallucinations that conflict with spatiotemporal evidence. Existing benchmarks mainly evaluate model

Candor-LR: A Dyadic Conversational Dataset for Audio-Visual Speech Recognition

model-releasesarxiv-cs-cv

arXiv:2609.10394v1 Announce Type: cross Abstract: Current audio-visual speech recognition (AVSR) benchmarks, like LRS3, rely heavily on clean, scripted and rehearsed speech. They fail to reflect the c

CARRE: Counterfactual Action Retrieval and Reason Evaluation for Explainable Churn Prescription

arXiv:2609.09766v1 Announce Type: new Abstract: Churn models typically identify high-risk customers but do not specify which feasible retention action should be considered or why that action is approp

researcharxiv-cs-cl

Cascading Gradient Inversion via LT-Code Inspired Peeling in Federated Learning

arXiv:2609.09659v1 Announce Type: new Abstract: Federated learning shares model updates rather than raw data, yet these updates can be inverted to reconstruct the clients' training data. Analytic reco

CAST: Canonical Approximate Schur Tree for Approximate Cholesky on Graphs

arXiv:2609.09255v1 Announce Type: cross Abstract: Graph-data workloads such as diffusion estimation, ranking, semi-supervised learning, and network optimization often solve many Laplacian or symmetric

Causal Attribution for Agentic Decisions: Estimators, Coupling, and a Traceability Specification

arXiv:2609.06445v1 Announce Type: new Abstract: A provider of a high-risk AI system must keep records that make a decision traceable, and for agentic systems it has not been established what those rec

agentsarxiv-cs-ai

CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows

arXiv:2609.07944v1 Announce Type: new Abstract: Existing causal-inference benchmarks for LLMs mostly score method descriptions or whether generated code runs, not whether the executed workflow recover

Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms

arXiv:2602.08751v4 Announce Type: replace Abstract: Motivation: Interpretability is not optional in biology: understanding gene regulation requires models whose learned structure can be directly inter

Characterizing Contention-Induced Reliability Collapse in KV-Cache Timing Side Channels for Multi-Tenant LLM Serving

arXiv:2609.06853v1 Announce Type: cross Abstract: Shared key--value (KV) cache reuse improves large language model (LLM) serving, but it can also create a timing side channel that reveals whether a pr

Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch

arXiv:2609.10525v1 Announce Type: cross Abstract: Language generation in the limit asks for valid unseen elements from every exhaustive positive presentation of an unknown infinite language. We charac

CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets

model-releasesarxiv-cs-cv

arXiv:2609.09510v1 Announce Type: cross Abstract: High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratific

CIPHER: Benchmarking Cross-record Inference over Privacy-Hardened Evidence Records

arXiv:2609.07022v1 Announce Type: cross Abstract: Reasoning over privacy-constrained records requires combining structured attributes with evidence from free-text narratives. We introduce CIPHER (Cros

Applications

CircuTutor: Transforming Static Circuit Problems into Intelligent and Dynamic Tutoring

arXiv:2609.08254v1 Announce Type: new Abstract: Learning direct current circuit concepts requires learners to connect invisible physical quantities, such as current, voltage, resistance, and power, wi

applicationsarxiv-cs-ai

CIT-CAD: Constraint Intent Tree-based CAD Code Generation and Verification

arXiv:2609.07434v1 Announce Type: new Abstract: Natural-language Computer-Aided Design (CAD) code generation aims to turn design intent into executable and editable parametric programs. Large language

researcharxiv-cs-ai

CityPlanner: A Sandbox Agent for Executable Urban Planning

arXiv:2609.09578v1 Announce Type: cross Abstract: Urban planning is a real-world spatial optimization problem that requires selecting feasible actions from large candidate spaces under practical objec

CIVI: A Framework for Diagnosing Search Agent Failures in Civic Information

arXiv:2609.08094v1 Announce Type: new Abstract: Large Language Models are increasingly deployed in public-sector settings, where incorrect guidance can cause irreversible harm. We introduce CIVI, the

CLAMP: Constrained Decoding for Vision-Language Embodied Planning

arXiv:2609.08602v1 Announce Type: new Abstract: Embodied planning increasingly relies on vision-language models (VLMs) to translate instructions and visual observations into executable action sequence

safetyarxiv-cs-ai

CLFTv2: Efficient Camera-LiDAR Fusion for Semantic Segmentation via Hierarchical Feature Pyramids

arXiv:2609.09881v1 Announce Type: new Abstract: Semantic segmentation for autonomous driving requires reliable detection of vulnerable road users (VRUs) despite heavy class imbalance. We introduce CLF

agentsarxiv-cs-cv

Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining

arXiv:2609.07798v1 Announce Type: cross Abstract: Natural Language Processing (NLP) in the climate domain requires models to process heterogeneous text sources, including scientific literature, policy

Closing the Consistency Gap: Self-Evolving Agents That Learn to Stay on Course

arXiv:2609.08832v1 Announce Type: new Abstract: Large language model (LLM)-powered agents can be accurate on average yet unreliable in production, a discrepancy that has been observed but remains larg

Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails

arXiv:2609.09134v1 Announce Type: new Abstract: Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic

Coastal Environment Generation with HoloOcean

arXiv:2609.10484v1 Announce Type: new Abstract: Marine robotic simulation provides a safe and inexpensive method of developing and testing algorithms for unmanned underwater vehicle (UUV) and unmanned

researcharxiv-cs-ro

CoGe-GCD: Reframing Generalized Category Discovery with Compositional Generalization

arXiv:2609.10158v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) assigns unlabeled instances, mixed with labeled data, to known or novel categories, requiring human-like compositio

safetyarxiv-cs-lg

CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification

arXiv:2604.25512v3 Announce Type: replace Abstract: In phishing detection, machine learning classifiers act as a first line of defense, but the false positives they produce are triaged by human analys

researcharxiv-cs-ai

Compact Visuotactile World Models for Lifting: Prediction, Reward Alignment, and Force Constraints

arXiv:2609.09597v1 Announce Type: new Abstract: Accurate contact prediction is useful for robotic manipulation only if it supports effective decisions. We investigate this connection using a compact,

safetyarxiv-cs-ro

CompassOPD: Cross-Family On-Policy Distillation via Within-Family Likelihood Shifts

arXiv:2609.10154v1 Announce Type: new Abstract: On-policy distillation (OPD) provides dense token-level supervision on student-generated trajectories. Although OPD performs strongly when teacher and s

safetyarxiv-cs-lg

Compiling VGDL into Causal Models

arXiv:2609.05459v1 Announce Type: new Abstract: Reinforcement learning and large language models often struggle to accurately capture the causal mechanics of game environments. Standard reinforcement

agentsarxiv-cs-ai

Complexity and Scale in AI-Assisted Workflow Management: A Federated Learning Case Study

arXiv:2606.18425v2 Announce Type: replace-cross Abstract: Federated learning over medical images is a demanding workflow application. Each round fans out across parallel client jobs and converges on a

Tutorials

Concept drift mitigation through community and spectral graph analysis for the detectionof cyberattacks in network traffic

arXiv:2609.09442v1 Announce Type: cross Abstract: In network traffic, legitimate behaviours and attack techniques evolve jointly - the phenomenon known as 'concept drift' [1]. Every detector is thereb

tutorialsarxiv-cs-lg

Applications

Concord: A Video Relational Algebra for Cross-Modal Query Optimization

arXiv:2609.05756v1 Announce Type: cross Abstract: Semantic video queries let users embed natural language prompts and use multimodal large language models (MLLMs) to interpret the video. Such queries

applicationsarxiv-cs-ai

ConsistencyAI: A Benchmark to Assess LLMs' Factual Consistency When Responding to Different Demographic Groups

arXiv:2510.13852v3 Announce Type: replace-cross Abstract: Is an LLM telling you different facts than it's telling me? This paper introduces ConsistencyAI, an independent benchmark for measuring the fa