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Computer Science & AI
Much of the new work in computer science and AI appears first as a preprint on arXiv. ReadSearch reads those listings every day, with papers OpenAlex files under the same subjects, and this page shows the newest it has, from machine learning and language to systems, theory and security.
The newest 1,000 papers, from 4 November 2026 to 5 November 2026: 1,000 arXiv preprints.
Newest papers, page 44
ArcRAG: Agentic Compositional Retrieval over Knowledge Graphs
Graph-based retrieval-augmented generation (GraphRAG) answers questions by retrieving over a knowledge graph built from a corpus.Computing Forest Degree Realizations with Minimum Cardinality Domination
In the Degree Realization problem with respect to a family $\mathcal{P}$ of graphs the input is a non-increasing sequence $d = (d_1,\ldots,d_n)$ of positive integers, and the goal is to decide…What Does Multi-Turn Reinforcement Learning Really Improve in LLM Agents?
While multi-turn agentic reinforcement learning (RL) excels on long-horizon tasks, its performance gains remain highly sensitive to interaction constraints.Object-independent evaluation of small-data astronomical image classifiers: architecture, representation, and acquisition shortcuts
Reported performance in small astronomical image datasets can reflect object reuse, field-of-view differences, acquisition settings, and catalogue-derived properties as well as astronomical…Model Merging Does Not Require Uniform LoRA Ranks
Model merging combines separately fine-tuned experts into a single model without retraining.Measuring the collaboration, not the agent
Benchmarks for visualization agents score the agent alone; the human only supplies reference answers.Risk-Sensitive Non-Parametric and Kernel Bandits
We study non-parametric bandits in which arms are evaluated using Cumulative Prospect Theory (CPT) rather than expected reward.FPTR: Feasibility-Preserving Transactional Refinement for Deadline-Constrained Joint Beam and Resource Allocation
Short-interval wireless schedulers must return a complete, feasible beam-and-resource allocation before each execution deadline, and a late or invalid output gives no utility in the current control…A $2.81^n$ upper bound on the number of stable matchings
We study the maximum number ${\rm SM}(n)$ of stable matchings in an instance with $n$ men and $n$ women.LibriSpeech-Real-QA: A Benchmark for Streaming Question Answering
Most speech large language models (SLMs) still process speech in an offline manner.Signed but Steerable: Measuring and Closing the Text-Vector Integrity Gap in Offline Retrieval-Augmented Generation
Offline retrieval-augmented generation (RAG) on edge devices is updated through signed knowledge packs that carry text and precomputed embedding vectors.Energy-Accumulate-Then-Act Backscatter Communications With Retransmission Under Imperfect Feedback Detection
In this paper, we propose a threshold-triggered energy-accumulate-then-act backscatter communication system with retransmission under imperfect feedback detection.Tools Need Not Speak in Text: Latent Context Compression for Agents
Large language model (LLM) agents typically append raw tool outputs to their context.CRESiST: Self-Enhancing Explorative Policy Learning for Simultaneous Speech Translation
Simultaneous Speech Translation (SimulST) requires balancing translation quality and latency.NaijaFacts: A Framework for Disentangling Language from Knowledge in Facts about Nigeria
Multilingual benchmarks for African languages mostly translate generic questions into local languages, measuring linguistic competence but not whether models know facts about Africa.Trace2Eval: Contextualized Evaluation of Coding Agents from Real-World Traces
Coding agents are increasingly used in real-world workflows across diverse domains, motivating evaluation grounded in real user tasks.ElecLoad: Adaptive Electricity Load Forecasting Guided by Multiple Events
Accurate electricity load forecasting provides critical decision support for energy procurement, generation scheduling, and supply-demand balancing, contributing to the economic efficiency and…Nowcasting Future Performance for Population Pruning in Survival-of-the-Fittest Training
Training high-performing neural networks often involves evaluating populations of candidate models with varying hyperparameters, architectures, or random seeds.HELIX: HEterogeneous LLM Inference with FleXible and Fine-Grained Partitioning
LLM inference is inherently heterogeneous, with performance bottlenecks shifting throughout inference phases down to individual operators.An Interaction-Aware Decision Framework for FDIC-Assisted Distressed Bank Acquisitions: Empirical Evidence from the FDIC Failed-Bank Panel and the SVB-First Citizens Case
Acquirers of failed banks weigh acquisition value, regulatory protection, risk, buyer strength, and execution difficulty jointly, because each signal's meaning depends on the others: high…
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