AI/ML arXiv cs.AI

Omni-Decision: A Progressive Evidence-State Agent System for Omni-Modal QA

Introduces Omni-Decision, a training-free system for omni-modal QA that uses a structured evidence-state to track and close evidence gaps across multiple modalities.

AI/ML arXiv cs.AI

The Ebb and Flow of Multimodal Focus: Scheduling Visual Relay Windows for Grounded VLM Reasoning

Proposes TRACE, a task-adaptive inference-time control framework that manages visual attention focus in VLMs to improve evidence-grounded reasoning.

AI/ML arXiv cs.AI

Enhancing Query Efficiency for d-DNNF Representations Through Preprocessing

Explores preprocessing techniques to improve query efficiency for d-DNNF representations of propositional formulas, specifically for sampling and model enumeration.

AI/ML arXiv cs.AI

Comparative Analysis of GAT and BERT for Human-Like Playtesting

Compares GAT and BERT architectures for modeling human-like playtesting in puzzle games, finding they better capture relational game board structures than CNNs.

AI/ML arXiv cs.AI

Learning Residual Kinematic Corrections for Continuous Neural Decoding via Reinforcement Learning

Presents a two-stage BCI decoding framework using RL to perform residual kinematic corrections on CNN-LSTM outputs for improved 3D motor imagery decoding.

Hardware/Chips arXiv cs.AI

HCRMap: Pressure-Aware Hot-Expert Residency Mapping for 3.5D MoE Chiplet Inference

Introduces HCRMap, a framework for MoE chiplet inference that dynamically manages hot expert replicas to reduce latency and communication bottlenecks.

AI/ML arXiv cs.AI

MAGIC: Transition-Aware Generation of Navigable Multi-Scene Game Worlds with Large Language Models

Presents MAGIC, a prompt-to-project system that uses LLMs to generate navigable, multi-scene game worlds with consistent transitions and connectivity.

AI/ML arXiv cs.AI

Interaction Scaling: Grounding the Third Axis of Test-Time Compute

Argues for 'interaction scaling' as a third axis of test-time compute, where models iteratively revise artifacts based on grounded external feedback.

AI/ML arXiv cs.AI

Auditing the Risk Claims of Distributional Reinforcement Learning

Audits distributional RL agents and finds that their claimed risk trade-offs are often training artifacts rather than reflections of environment stochasticity.

Software Engineering Hacker News

Understanding the Go Runtime: Profiling

A discussion on profiling the Go runtime to understand its internal workings.

Other Hacker News

European "age verification" "app" forcing everyone to use Android or iOS

Criticism of a European age verification app that restricts users to Android or iOS, raising concerns about platform lock-in and accessibility.

AI/ML arXiv cs.AI

Efficient Test-Time Optimization for Multi-Agent Proof Autoformalization

Introduces ToMap, a multi-agent framework for proof autoformalization that optimizes test-time compute by focusing on the 'Decomposer' agent.

AI/ML arXiv cs.AI

Calibrated e-CUSUM Decoding for Quantized Reasoning Models: Why Token Log-Probability Is the Wrong Observable for Decoding Monitors

Presents a new decoding controller for quantized reasoning models that replaces token log-probability with a calibrated e-CUSUM detector to better identify failing traces.

AI/ML arXiv cs.AI

Verifier-Guided Twelve-Tone Composition: A Generate-Verify-Repair Harness for Symbolic Music Generation

Develops a neuro-symbolic harness using a generate-verify-repair loop to improve the consistency and quality of twelve-tone symbolic music generation with LLMs.

AI/ML arXiv cs.AI

AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic

Introduces AutoVSR, a framework that converts circuit schematics to symbolic expressions using VLMs and a symbolic solver with an executable intermediate representation.

AI/ML arXiv cs.AI

Compile, Then Page: Executable SOP Programs and a Capability-Gated Runtime for Procedural LLM Agents

Proposes a method to compile SOP constraints into executable pseudo-code for LLM agents, using a capability-gated runtime to improve adherence to safety-critical procedures.

AI/ML arXiv cs.AI

From Neural Network Decisions to Training Cases: An Exact Account via Case-Based Decision Theory

Provides a mathematical account of neural network decisions using Case-Based Decision Theory, allowing audit signals to trace scores back to training cases without retraining.

AI/ML arXiv cs.AI

OpsMem: Dual-Memory Reasoning with Cross-Memory Resonance for Failure Diagnosis

Presents OpsMem, a dual-memory framework for software failure diagnosis that coordinates current diagnostic state with long-term operational experience via cross-memory resonance.

AI/ML arXiv cs.AI

StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure

Introduces StructAgent, a state-centered framework that uses unified causal structures and verifier-backed transitions to improve LLM/VLM performance on long-horizon digital tasks.

Other Hacker News

Just Let Me Write Digits

A Hacker News discussion thread focused on the frustrations of writing numerical digits in a specific software context.