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Beam Search as Test-Time Self-Distillation via Counterfactual Contexts

arXiv:2609.37041v1 Announce Type: cross Abstract: Self-Distillation Fine-Tuning (SDFT) enables a language model to act as its own teacher: by conditioning on a demonstration, the model produces an imp

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Model Releases

BeatDance: Generating Beat-Consistent 3D Dance with Hierarchical Spatial-Temporal Modeling

DGX agent

arXiv:2609.37400v1 Announce Type: new Abstract: Generating realistic 3D dance from music is a challenging task that requires accurate synchronization with musical rhythms while capturing the spatial c

model-releasesarxiv-cs-cv

30 Sept 2026

Behavioral Capacity Certificates for Quantized Language Models

arXiv:2609.37887v1 Announce Type: new Abstract: Activation and key-value cache precision change what a quantized language model computes without altering its stored weights. Direct weight-code bounds,

researcharxiv-cs-lg

Behavioral Convergence Without Representational Convergence: Persistent Training-History Dependence in Neural Networks

arXiv:2609.37836v1 Announce Type: new Abstract: Neural networks trained toward the same final objective can reach similar predictive performance while retaining internal representations shaped by earl

researcharxiv-cs-lg

Benchmarking Automatic Speech Recognition Tools for Iberian Languages

arXiv:2609.36920v1 Announce Type: new Abstract: Comprehensive evaluations of automatic speech recognition (ASR) for Iberian languages remain limited, and low-resource languages, biases, and efficiency

Tutorials

Benchmarking graph-based models for in-silico toxicity prediction in drug discovery

arXiv:2609.37555v1 Announce Type: new Abstract: Drug discovery is a costly and high-risk process, where toxicity-related failures remain a major cause of attrition in both preclinical and clinical sta

tutorialsarxiv-cs-lg

Benchmarking Vision-Language Models on Synapse Detection and Proofreading in Connectomics

arXiv:2609.36492v1 Announce Type: cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse dete

Tutorials

Best Practices in EEG Analysis: Preprocessing, Modeling, and Machine Learning

arXiv:2609.36609v1 Announce Type: cross Abstract: Electroencephalography (EEG) analysis requires careful choices in preprocessing, statistical modeling, and machine learning because EEG signals are hi

tutorialsarxiv-cs-lg

Better Behavioral Prediction, More Faithful Model Ablations? Evidence from Sequential Choice

arXiv:2609.36097v1 Announce Type: cross Abstract: Using predictive models to explain cognition requires more than accurate behavioral predictions. Input ablations offer an appealing route: remove info

Better Nearest Neighbor Graph Indices via (Efficient) LLM-Guided Pruning

arXiv:2609.36359v1 Announce Type: new Abstract: Graph-based approximate nearest neighbor search (ANNS) is widely used for large-scale semantic search. Its indices are constructed primarily based on ge

Local Ai

Beyond a single latent space: a dual-latent world model for long-horizon planning

arXiv:2609.37644v1 Announce Type: new Abstract: Latent world models often struggle with long-horizon planning despite accurate short-term predictions. Recursive rollouts accumulate errors, while dista

local-aiarxiv-cs-ai

Beyond Attention Imbalance: Mitigating Hallucinations via Spectral Surgery

arXiv:2609.37263v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs) achieve remarkable success, hallucinations remain a significant barrier to their reliable deployment. Recent

researcharxiv-cs-cv

Beyond Binary Preferences: Graded Preference Optimization for Limb-Motion Captioning

model-releasesarxiv-cs-cv

arXiv:2609.36628v1 Announce Type: new Abstract: Vision-Language Models (VLMs) can generate rich video captions, yet often misidentify which person performs an action or which limb is involved, particu

Beyond Compression: Diagnosing How Post-Training Changes Mathematical Reasoning

arXiv:2609.37066v1 Announce Type: cross Abstract: Post-training is central to mathematical reasoning in modern large language models (LLMs), but endpoint pass@1 alone underidentifies what has changed.

Applications

Beyond Conditional Independence: Root Cause Analysis with Deep Causal Models

arXiv:2609.36771v1 Announce Type: cross Abstract: Root cause analysis (RCA) is a critical problem in many real-world scenarios. RCA enables the identification of faulty or failing mechanisms in a syst

applicationsarxiv-cs-ai

Applications

Beyond Discrimination: Calibrated Geoprior Fusion for Bioacoustic Monitoring

arXiv:2609.35863v1 Announce Type: cross Abstract: Modern bioacoustic foundation models like Perch and BirdNET can identify species with high discriminative accuracy, yet their confidence scores are of

applicationsarxiv-cs-lg

Beyond Interaction Capacity: Estimator Scaling with Recursive Models for CTR Prediction

arXiv:2609.37905v1 Announce Type: cross Abstract: Click-Through Rate prediction, a core task in recommendation and advertising systems, relies on modeling interactions among sparse categorical feature

Beyond Keywords: Leveraging Generative LLMs and Label Aggregation to Classify Economic Policy Uncertainty in News Articles

arXiv:2609.35856v1 Announce Type: cross Abstract: This research describes the adaptation of Large Language Models (LLMs) for economic monitoring in the public sector to automatically determine whether

Beyond Legibility: Benchmarking Visual Text Rendering and In-Place Editing in Unified Video Generation

model-releasesarxiv-cs-cv

arXiv:2609.36598v1 Announce Type: new Abstract: A video can exhibit convincing motion and photorealism yet fail immediately when visual text collapses. Unlike generic scene content, visual text is unf

Beyond Lip Sync: Reference-Grounded Oral Refinement for Audio-Driven Portrait Animation

model-releasesarxiv-cs-cv

arXiv:2609.38019v1 Announce Type: new Abstract: We present RGOR (Reference-Grounded Oral Refinement), an audio-driven lip-sync framework that renders the mouth of the specific person being dubbed rath

Beyond Low-Rank Parameterization: Narrowing the Gap Between LoRA and Full Fine-Tuning via Gradient Decomposition

arXiv:2609.37027v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) is a widely used approach to parameter-efficient fine-tuning (PEFT), yet a performance gap can remain relative to full fine-t

Beyond Pixels: A Vector-to-Graph Framework for Reliable Schematic Auditing

arXiv:2602.11678v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual understanding, yet they suffer from a critical limitation: structu

Beyond Prompt Count: How Data Shapes Transfer in On-Policy Distillation

arXiv:2609.37377v1 Announce Type: new Abstract: On-policy distillation (OPD) trains students using teacher feedback on their own sampled responses, yet how prompt choice shapes transfer across teacher

Beyond Readability: Evaluating Task Information Recoverability

arXiv:2609.36957v1 Announce Type: new Abstract: Direct visual readability and task-information recoverability are different quantities. Failure to decode a target from a fixed observation need not eli

researcharxiv-cs-cv

Beyond Rule-Based Mutation Testing: Test-Aware Mutant Generation Using Large Language Models

arXiv:2609.35841v1 Announce Type: cross Abstract: Mutation testing evaluates test-suite adequacy by injecting synthetic faults into program code. However, traditional rule-based tools often generate l

Beyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoods

arXiv:2609.37218v1 Announce Type: cross Abstract: Semantic watermarking improves robustness against watermark removal attacks by embedding detectable signals into sentence-level representations. Howev

Beyond Semantics: How Temporal Biases Shape Retrieval in Transformer and State-Space Models

arXiv:2510.22752v2 Announce Type: replace-cross Abstract: In-context learning is governed by both temporal and semantic relationships, shaping how Large Language Models (LLMs) retrieve contextual info

Beyond Sub-Gaussian Detector Scores: Robust Weighted Profile-Loss Change Point Detection for Human-LLM Text Segmentation

arXiv:2609.36888v1 Announce Type: new Abstract: Mixed human-LLM documents require locating authorship transitions from detector scores whose reliability varies across text units. Existing weighted mea

Beyond Symmetric Agents: Cognitive Diversity and Multi-Agent Debate in Small Language Models

arXiv:2609.35875v1 Announce Type: new Abstract: Multi-agent debate (MAD) reportedly improves reasoning and factuality over single-model inference, but prior work treats agents as symmetric peers, leav

Beyond the Context Window: An Adaptive Entropy-Based Routing Framework for Hybrid Retrieval and Long-Context Language Models

arXiv:2609.35831v1 Announce Type: new Abstract: Modern large language models now support context windows of more than one million tokens, which has raised the question of whether retrieval-augmented g

Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies

arXiv:2609.38155v1 Announce Type: cross Abstract: Answering questions about long videos often requires connecting events involving the same objects across hours or days. Chronological descriptions and

Beyond Token Importance: Preserving Spatial Scaffolds for Efficient Vision-Language-Action Inference

arXiv:2609.36967v1 Announce Type: new Abstract: Existing VLA pruning strategies primarily select individual visual tokens according to task-level semantic relevance, while overlooking the spatial info

researcharxiv-cs-ro

Bias-variance decompositions: the exclusive privilege of Bregman divergences

arXiv:2501.18581v5 Announce Type: replace Abstract: Bias-variance decompositions are widely used to understand the generalization performance of machine learning models. While the squared error loss p

safetyarxiv-cs-lg

Hardware

BiFE: Search-Efficient Discovery of CPU-Only Branching Policies via LLM-based Bi-Fidelity Evolution

arXiv:2609.36735v1 Announce Type: new Abstract: In branch-and-bound (B&B) for mixed-integer linear programming (MILP), branching variable selection critically impacts efficiency. Existing neural branc

hardwarearxiv-cs-ai

Tutorials

Bilinear World Models: Learning Representations with Structured Dynamics for Efficient Control

arXiv:2609.36305v1 Announce Type: new Abstract: World models jointly learn latent representations and dynamics that predict how high-dimensional observations evolve under actions. In this work, we pro

tutorialsarxiv-cs-ro

Billiger.de Products: A Bilingual Entity Matching Benchmark

arXiv:2609.37713v1 Announce Type: new Abstract: Existing product matching benchmarks primarily contain English-language product data and are often dominated by a single product category, such as elect

Binarization Flattens the Score Space

arXiv:2609.35797v1 Announce Type: cross Abstract: Large language model (LLM) judges are often used as rewards to train policies on objectives that deterministic verifiers cannot capture. However, thes

BITEM at the NTCIR-19 R2C2 Task: Predicting Confidence from Agentic RAG Pipeline Signals

arXiv:2609.37993v1 Announce Type: cross Abstract: The BITEM team entered both subtasks of the NTCIR-19 R2C2 task with a single agentic pipeline, in which a model searches, reads and records evidence o

Bits Under ZK-LLM: Evaluating Zero-Knowledge-Friendly Quantization for Verifiable Private LLM Inference

arXiv:2609.36437v1 Announce Type: new Abstract: Zero-knowledge proofs are emerging as a promising approach for enabling private, verifiable LLM governance and auditing, where regulators, users, and au

BlenDAgger: Blended Shared Control for Interactive Imitation Learning

arXiv:2609.37599v1 Announce Type: new Abstract: Robot policies are frequently trained from human corrections, yet teleoperating a robot to provide corrections is burdensome, and human demonstrators ar

safetyarxiv-cs-ro

Block Sparse Flash Attention

arXiv:2512.07011v2 Announce Type: replace-cross Abstract: Modern large language models increasingly require long contexts for reasoning and multi-document tasks, but attention's quadratic complexity c

Boids of a Feather Flock Together - Evolving Prey Behaviours Under Different Predator Attack Strategies

arXiv:2609.37885v1 Announce Type: cross Abstract: Flocking and schooling are thought to have evolved partly as defences against predation, but how prey should balance social and escape tendencies may

Boosting Adversarial Robustness and Generalization with Dictionary Structure

arXiv:2502.00834v2 Announce Type: replace Abstract: This work investigates a novel approach to boost adversarial robustness and generalization by incorporating structural prior into the design of deep

researcharxiv-cs-lg

Boosting Metric Depth Completion via Training-Free Adaptive Response Geometry

arXiv:2609.36168v1 Announce Type: new Abstract: Depth completion aims to recover dense metric depth from sparse sensor measurements, increasingly leveraging visual foundation models as geometric prior

researcharxiv-cs-cv

Bootstrapping Audiovisual Speech Recognition in Zero-AV-Resource Scenarios

arXiv:2603.08249v2 Announce Type: replace-cross Abstract: Audiovisual speech recognition (AVSR) combines acoustic and visual cues to improve transcription robustness under challenging conditions but r

Boundary-State Control for Tool-Using Language-Model Agents: Commit-Time Consistency under State Drift

arXiv:2609.37475v1 Announce Type: new Abstract: Tool-using language-model agents can decide that an action is permissible and execute it only after security-relevant state has changed. We study this p

Brain-SAD: A Brain-Inspired Safe Autonomous Driving Control Framework with Dynamic Fear-Oriented Constraint on Dual-Policy

arXiv:2609.38016v1 Announce Type: new Abstract: Constrained Reinforcement Learning has recently gained increasing attention in the field of Safe Autonomous Driving, where the general mechanism is to m

BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization

arXiv:2609.37956v1 Announce Type: new Abstract: Brain networks characterize structural and functional relationships among brain regions and support research on cognition, brain disorders, and brain-co