· ai
[Paper] SUPN: Shallow Universal Polynomial Networks
Deep neural networks (DNNs) and Kolmogorov-Arnold networks (KANs) are popular methods for function approximation due to their flexibility and expressivity. Howe...
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- · ai
[Paper] Subjective Depth and Timescale Transformers: Learning Where and When to Compute
The rigid, uniform allocation of computation in standard Transformer (TF) architectures can limit their efficiency and scalability, particularly for large-scale...
- · ai
[Paper] Text-to-SQL as Dual-State Reasoning: Integrating Adaptive Context and Progressive Generation
Recent divide-and-conquer reasoning approaches, particularly those based on Chain-of-Thought (CoT), have substantially improved the Text-to-SQL capabilities of ...
- · ai
[Paper] Training Introspective Behavior: Fine-Tuning Induces Reliable Internal State Detection in a 7B Model
Lindsey (2025) investigates introspective awareness in language models through four experiments, finding that models can sometimes detect and identify injected ...
- · ai
[Paper] Prune4Web: DOM Tree Pruning Programming for Web Agent
Web automation employs intelligent agents to execute high-level tasks by mimicking human interactions with web interfaces. Despite the capabilities of recent La...
- · ai
[Paper] Monet: Reasoning in Latent Visual Space Beyond Images and Language
'Thinking with images' has emerged as an effective paradigm for advancing visual reasoning, extending beyond text-only chains of thought by injecting visual evi...
- · software
[Paper] Large Language Models for Unit Test Generation: Achievements, Challenges, and the Road Ahead
Unit testing is an essential yet laborious technique for verifying software and mitigating regression risks. Although classic automated methods effectively expl...
- · software
[Paper] Multi-Agent Systems for Dataset Adaptation in Software Engineering: Capabilities, Limitations, and Future Directions
Automating the adaptation of software engineering (SE) research artifacts across datasets is essential for scalability and reproducibility, yet it remains large...
- · ai
[Paper] Thinking With Bounding Boxes: Enhancing Spatio-Temporal Video Grounding via Reinforcement Fine-Tuning
Spatio-temporal video grounding (STVG) requires localizing a target object in untrimmed videos both temporally and spatially from natural language descriptions....
- · ai
[Paper] PFF-Net: Patch Feature Fitting for Point Cloud Normal Estimation
Estimating the normal of a point requires constructing a local patch to provide center-surrounding context, but determining the appropriate neighborhood size is...
- · ai
[Paper] The Directed Prediction Change - Efficient and Trustworthy Fidelity Assessment for Local Feature Attribution Methods
The utility of an explanation method critically depends on its fidelity to the underlying machine learning model. Especially in high-stakes medical settings, cl...
- · ai
[Paper] Hybrid-AIRL: Enhancing Inverse Reinforcement Learning with Supervised Expert Guidance
Adversarial Inverse Reinforcement Learning (AIRL) has shown promise in addressing the sparse reward problem in reinforcement learning (RL) by inferring dense re...