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Artificial Intelligence
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The newest 5,000 papers, from 11 October 2026 to 5 November 2026: 4,998 arXiv preprints and 2 OpenAlex records.
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Newest papers, page 176
Aligning Language Models with Indigenous Community Cosmovision through Constitutional AI
Large language models (LLMs) are predominantly trained on corpora that reflect Western, anglophone worldviews.Learning When to Abort in Transformer Planning: A Mechanistic Study
Planning does not by itself imply the ability to recognise errors, but recognising errors can improve planning capacity.Shared-Private Cross-Modal Discrepancy Learning for Imbalanced Multi-Source Audio-Visual Deepfake Detection
Audio-visual deepfake detectors are often trained under a single dataset or manipulation regime, but multi-source training collections may contain heterogeneous attacks and uneven source…AdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection
Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars.Where and Why Search-Augmented LLMs Fail When Reasoning over Rapidly Evolving Knowledge
As the world changes, new information is published while older records remain online.Formally Verified Autoresearch for Analyzing the Expressivity of Multi-Head Attention
Multi-head attention is a central component of the transformer architecture, yet how its expressivity depends on the number of heads remains poorly understood.Local Evidence, Global Failure: Diagnosing Speech-Vision Temporal Composition in Audio-Visual Language Models
Audio-visual large language models (AV-LLMs) can fail at full-video speech-vision decisions even when useful visual evidence is locally recoverable.CHSM8: A Chess Transformer that Follows Natural-Language Style Prompts
We present CHSM8, a 210M-parameter chess transformer that plays moves conditioned on a free-text description of a playing style, e.g. "go for the Sicilian Defense", "solid, safe, risk-free chess" or…CD-OPD: Contextual Digest for On-Policy Distillation
Teacher takeover in on-policy distillation (OPD) can produce incorrect responses even when the student and teacher independently answer the same problem correctly, a failure we quantify using…Aligning Cultural Behaviors in Arabic Language Models via Preferences
Arabic LLMs have improved rapidly, but aligning them with country-specific cultural behavioral preferences remains underexplored.MemDerive: A Diagnostic Benchmark for Agent Memory over Evolving Data
Long-running agents rely on memory of their past interactions for task state, such as what has been completed and which conditions still hold.Outcome-Anchored Credit Reallocation for Agentic Knowledge Graph Question Answering
Agentic knowledge graph question answering (KGQA) requires large language models (LLMs) to solve complex questions through multi-turn interactions with a knowledge graph (KG).When Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Logical Structure
Large language models (LLMs) have achieved strong performance across diverse reasoning tasks, yet it remains unclear whether this performance reflects an understanding of underlying logical…MOSAIC: Multi-Objective Search for Allocating Inference Cache Across LLM Decoder Layers
The Key-Value (KV) cache is the main memory bottleneck of long-context LLM inference.Stepwise Reasoning Verification: Don't Generate, Classify!
Verifying the reasoning of large language models is increasingly important as they are applied to complex mathematical and scientific problems.Enhanced Masked Diffusion Unlearning
Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens with bidirectional context.System X: An LLM Decision Model That Replies from Its Own KV Cache
Decision models return probabilities over supplied options, but a deployed agent may also need to reply in words.Reliability-Preserving Compression for Deployable Medical Image Segmentation
Post-training compression of pretrained medical segmentation models commonly uses quantization, pruning, or distillation to reduce model size and computational cost.DiaLong: Benchmarking Reminiscence in Long-Context Dialogues
How well can transformer-based Large Language Models (LLMs) retain and recall memories in long contexts of dialogue?On Reasoning Correctness Directions
We present experimental evidence suggesting that information about whether a model's reasoning is on the right track can be linearly decodable without defining a causally useful direction for…