- HyperMem: Hypergraph Memory for Long-Term Conversations
Juwei Yue, Chuanrui Hu, Jiawei Sheng, Zuyi Zhou, Wenyuan Zhang · Apr 9, 2026 · Citations: 0
Llm As JudgeAutomatic Metrics General
Long-term memory is essential for conversational agents to maintain coherence, track persistent tasks, and provide personalized interactions across extended dialogues.
- VRM: Teaching Reward Models to Understand Authentic Human Preferences
Biao Liu, Ning Xu, Junming Yang, Hao Xu, Xin Geng · Mar 5, 2026 · Citations: 0
Human Eval General
Large Language Models (LLMs) have achieved remarkable success across diverse natural language tasks, yet the reward models employed for aligning LLMs often encounter challenges of reward hacking, where the approaches predominantly rely on…
- The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration
Kotaro Furuya, Yuichi Kitagawa · Oct 30, 2025 · Citations: 0
Automatic Metrics General
While a multi-agent approach based on large language models (LLMs) represents a promising strategy to surpass the capabilities of single models, its success is critically dependent on synergistic team composition.
- Embodied Task Planning via Graph-Informed Action Generation with Large Language Models
Xiang Li, Ning Yan, Masood Mortazavi · Jan 29, 2026 · Citations: 0
Simulation Env General
We propose GiG, a planning framework that structures embodied agents' memory using a Graph-in-Graph architecture.
- Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering
Xinyu Zhu, Yuzhu Cai, Zexi Liu, Bingyang Zheng, Cheng Wang · Jan 15, 2026 · Citations: 0
Simulation Env General
The advancement of artificial intelligence toward agentic science is currently bottlenecked by the challenge of ultra-long-horizon autonomy, the ability to sustain strategic coherence and iterative correction over experimental cycles spanni
- Not All That Is Fluent Is Factual: Investigating Hallucinations of Large Language Models in Academic Writing
Humam Khan, Md Tabrez Nafis, Shahab Saquib Sohail, Aqeel Khalique, Rehan Hasan Khan · May 5, 2026 · Citations: 0
Automatic Metrics General
Some of the most widely used evaluation metrics often fail to check errors which alter sentiment in machine-translated text.
- Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders
Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, Claudia Shi, Achille Nazaret · Jul 31, 2025 · Citations: 0
Automatic Metrics General
To properly evaluate MTM topics against word list approaches, we propose topic judge, an LLM-based pairwise comparison evaluation framework.
- Reasoning or Rhetoric? An Empirical Analysis of Moral Reasoning Explanations in Large Language Models
Aryan Kasat, Smriti Singh, Aman Chadha, Vinija Jain · Mar 23, 2026 · Citations: 0
Llm As Judge General
Using an LLM-as-judge scoring pipeline validated across three judge models, we classify more than 600 responses from 13 LLMs spanning a range of architectures, parameter scales, and training regimes across six classical moral dilemmas, and…
- SWAN: Semantic Watermarking with Abstract Meaning Representation
Ziping Ye, Gourab Dey, Christos Christodoulopoulos, Charith Peris, Anil Ramakrishna · May 5, 2026 · Citations: 0
Automatic Metrics General
In contrast to existing watermarking methods, which typically encode signatures by adjusting token selection preferences during text generation, SWAN embeds the signature directly in the sentence's semantic representation.
- Preference Heads in Large Language Models: A Mechanistic Framework for Interpretable Personalization
Weixu Zhang, Ye Yuan, Changjiang Han, Yuxing Tian, Zipeng Sun · Apr 24, 2026 · Citations: 0
Automatic Metrics General
In this work, we adopt a mechanistic interpretability perspective and hypothesize the existence of a sparse set of Preference Heads, attention heads that encode user specific stylistic and topical preferences and exert a causal influence on…
- PLOT: Enhancing Preference Learning via Optimal Transport
Liang Zhu, Yuelin Bai, Xiankun Ren, Jiaxi Yang, Lei Zhang · Apr 2, 2026 · Citations: 0
Automatic Metrics General
Preference learning in Large Language Models (LLMs) has advanced significantly, yet existing methods remain limited by modest performance gains, high computational costs, hyperparameter sensitivity, and insufficient modeling of global…
- BeliefShift: Benchmarking Temporal Belief Consistency and Opinion Drift in LLM Agents
Praveen Kumar Myakala, Manan Agrawal, Rahul Manche · Mar 25, 2026 · Citations: 0
Automatic Metrics General
LLMs are increasingly used as long-running conversational agents, yet every major benchmark evaluating their memory treats user information as static facts to be stored and retrieved.
- StoryBox: Collaborative Multi-Agent Simulation for Hybrid Bottom-Up Long-Form Story Generation Using Large Language Models
Zehao Chen, Rong Pan, Haoran Li · Oct 13, 2025 · Citations: 0
Simulation Env General
Human writers often begin their stories with an overarching mental scene, where they envision the interactions between characters and their environment.
- $\texttt{YC-Bench}$: Benchmarking AI Agents for Long-Term Planning and Consistent Execution
Muyu He, Adit Jain, Anand Kumar, Vincent Tu, Soumyadeep Bakshi · Apr 1, 2026 · Citations: 0
Automatic Metrics General
As LLM agents tackle increasingly complex tasks, a critical question is whether they can maintain strategic coherence over long horizons: planning under uncertainty, learning from delayed feedback, and adapting when early mistakes compound.
- QChunker: Learning Question-Aware Text Chunking for Domain RAG via Multi-Agent Debate
Jihao Zhao, Daixuan Li, Pengfei Li, Shuaishuai Zu, Biao Qin · Mar 12, 2026 · Citations: 0
Automatic Metrics General
Drawing inspiration from Hal Gregersen's "Questions Are the Answer" theory, we design a multi-agent debate framework comprising four specialized components: a question outline generator, text segmenter, integrity reviewer, and knowledge…
- Memory Contagion: Cross-Temporal Propagation of Evaluator Bias via Agent Memory
Zewen Liu · Jun 22, 2026 · Citations: 0
General
We show that when agents are trained or guided by biased evaluators, their experiences become biased; when these trajectories are stored and consolidated into memory, the bias propagates to future agents retrieving from the same memory…
- Discourse Coherence and Response-Guided Context Rewriting for Multi-Party Dialogue Generation
Zhiyu Cao, Peifeng Li, Qiaoming Zhu · Apr 8, 2026 · Citations: 0
General
Specifically, DRCR employs two complementary feedback signals, discourse coherence and response quality, to construct preference data for both context rewriting and response generation.
- Not All Queries Need Deep Thought: CoFiCot for Adaptive Coarse-to-fine Stateful Refinement
Dongxu Zhang, Hongqiang Lin, Yiding Sun, Pengyu Wang, Qirui Wang · Mar 9, 2026 · Citations: 0
Automatic Metrics General
To address this, we propose CoFiCot, a coarse-to-fine adaptive framework that dynamically tailors inference strategies to problem difficulty.
- LayerT2V: A Unified Multi-Layer Video Generation Framework
Guangzhao Li, Kangrui Cen, Baixuan Zhao, Yi Xin, Siqi Luo · Aug 6, 2025 · Citations: 0
Automatic Metrics General
Text-to-video generation has advanced rapidly, but existing methods typically output only the final composited video and lack editable layered representations, limiting their use in professional workflows.
- Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
Justin Lovelace, Christian Belardi, Sofian Zalouk, Adhitya Polavaram, Srivatsa Kundurthy · Feb 24, 2026 · Citations: 0
Llm As JudgeAutomatic Metrics General
Evaluations show STAR-LDM significantly outperforms similar-sized models on language understanding benchmarks and achieves >70\% win rates in LLM-as-judge comparisons for narrative coherence and commonsense reasoning.
