· ai
[Paper] Modeling LLM Agent Reviewer Dynamics in Elo-Ranked Review System
In this work, we explore the Large Language Model (LLM) agent reviewer dynamics in an Elo-ranked review system using real-world conference paper submissions. Mu...
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- · ai
[Paper] Multiplex Thinking: Reasoning via Token-wise Branch-and-Merge
Large language models often solve complex reasoning tasks more effectively with Chain-of-Thought (CoT), but at the cost of long, low-bandwidth token sequences. ...
- · ai
[Paper] APEX-SWE
We introduce the AI Productivity Index for Software Engineering (APEX-SWE), a benchmark for assessing whether frontier AI models can execute economically valuab...
- · ai
[Paper] Asymptotic Universal Alignment: A New Alignment Framework via Test-Time Scaling
Aligning large language models (LLMs) to serve users with heterogeneous and potentially conflicting preferences is a central challenge for personalized and trus...
- · ai
[Paper] Rewarding the Rare: Uniqueness-Aware RL for Creative Problem Solving in LLMs
Reinforcement learning (RL) has become a central paradigm for post-training large language models (LLMs), particularly for complex reasoning tasks, yet it often...
- · ai
[Paper] Spatial Context Improves the Integration of Text with Remote Sensing for Mapping Environmental Variables
Recent developments in natural language processing highlight text as an emerging data source for ecology. Textual resources carry unique information that can be...
- · ai
[Paper] To Retrieve or To Think? An Agentic Approach for Context Evolution
Current context augmentation methods, such as retrieval-augmented generation, are essential for solving knowledge-intensive reasoning tasks.However, they typica...
- · ai
[Paper] TableCache: Primary Foreign Key Guided KV Cache Precomputation for Low Latency Text-to-SQL
In Text-to-SQL tasks, existing LLM-based methods often include extensive database schemas in prompts, leading to long context lengths and increased prefilling l...
- · ai
[Paper] Inferring Latent Intentions: Attributional Natural Language Inference in LLM Agents
Attributional inference, the ability to predict latent intentions behind observed actions, is a critical yet underexplored capability for large language models ...
- · ai
[Paper] From Rows to Reasoning: A Retrieval-Augmented Multimodal Framework for Spreadsheet Understanding
Large Language Models (LLMs) struggle to reason over large-scale enterprise spreadsheets containing thousands of numeric rows, multiple linked sheets, and embed...
- · ai
[Paper] Learner-Tailored Program Repair: A Solution Generator with Iterative Edit-Driven Retrieval Enhancement
With the development of large language models (LLMs) in the field of programming, intelligent programming coaching systems have gained widespread attention. How...
- · ai
[Paper] Do You Understand How I Feel?: Towards Verified Empathy in Therapy Chatbots
Conversational agents are increasingly used as support tools along mental therapeutic pathways with significant societal impacts. In particular, empathy is a ke...