5. Stress Testing Large Reasoning Models Proposes a new benchmark framework called REST to evaluate the robustness of Large Reasoning Models (LRMs) under multi-question stress.
@dair_ai
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Agentic-R1: 7B Language Model with Dynamic Tool-Based Reasoning
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3. Agentic-R1 This paper introduces Agentic-R1, a 7B language model trained to dynamically switch between tool-based execution and pure text reasoning using a novel fine-tuning framework called DualDistill.
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Chain-of-Thought Monitorability for AI Safety Oversight
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4. Chain-of-Thought Monitorability Proposes that language-based CoT reasoning in LLMs offers an opportunity for AI safety by enabling automated oversight of models’ internal reasoning processes.
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Study Evaluates LLM Performance Across Extended Context Lengths
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2. Context Rot This comprehensive study by Chroma evaluates how state-of-the-art LLMs perform as input context length increases, challenging the common assumption that longer contexts are uniformly handled.
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xLSTMAD: Anomaly Detection for Multivariate Time Series
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10. xLSTMAD This paper introduces xLSTMAD, the first anomaly detection method using an encoder-decoder xLSTM architecture tailored for multivariate time series.
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NaturalThoughts: Reasoning Traces Dataset from DeepSeek-R1
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8. NaturalThoughts This paper introduces NaturalThoughts, a large-scale dataset of reasoning traces distilled from DeepSeek-R1 using questions from the NaturalReasoning corpus.
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Visual Structures Enhance GPT-4o Feature Binding Reasoning
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9. Visual Structures Help Visual Reasoning This study shows that adding simple spatial structures (like horizontal lines) to images significantly boosts GPT-4o’s visual reasoning by improving feature binding.
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Evaluating LLM-Based Agents: Key Metrics and Methods
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7. Survey on Evaluation of LLM-based Agents Overview of how to evaluate LLM-based agents, which differ significantly from traditional LLMs by maintaining memory, planning over multiple steps, using tools, and interacting with dynamic environments.
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Deep Research Agents: Comprehensive Survey of LLM-Powered Systems
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6. Deep Research Agents Provides the most comprehensive survey to date of Deep Research (DR) agents, LLM-powered systems built for autonomous, multi-step informational research.
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Comprehensive Threat Model for LLM-Powered AI Agent Ecosystems
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5. Threats in LLM-Powered AI Agents Workflows This work presents the first comprehensive, end-to-end threat model for LLM-powered agent ecosystems.