Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA (2024 · 72 citations)
Most current long-context benchmarks make inputs longer by padding them with unrelated filler text. In those setups, the evidence for an answer usually sits in one place, so a model can skip most of the input and still answer correctly. Wang et al. address this with Loong, a multi-document QA benchmark where every…
ExpSeek: Self-Triggered Experience Seeking for Web Agents (2026 · 24 citations)
Web agents that search the open web often explore poorly or answer too early, particularly when built on small LLMs.
EvoRoute: Experience-Driven Self-Routing LLM Agent Systems (2026 · 2 citations)
Multi-model agentic systems for deep research perform well but often run slowly and cost a lot. The authors frame this as the Agent System Trilemma : it is hard to get high accuracy, low monetary cost and fast completion at the same time. Their solution, EvoRoute , chooses an LLM backbone for every individual step of…

Co-authors here

12 of 16 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 84 times (of the 149,439 papers whose bibliographies we read); 26 citing papers with a page here →.

Updated 1 November 2026